├── Code ├── Chapter_10_Lab.R ├── Chapter_2_Lab.R ├── Chapter_3_Lab.R ├── Chapter_4_Lab.R ├── Chapter_5_Lab.R ├── Chapter_6_Lab.R ├── Chapter_7_Lab.R ├── Chapter_8_Lab.R └── Chapter_9_Lab.R ├── Data ├── Advertising.csv ├── Auto.csv ├── Auto.data ├── Ch10Ex11.csv ├── College.csv ├── Credit.csv ├── Heart.csv ├── Income1.csv └── Income2.csv ├── README.md └── sample.pdf /Code/Chapter_10_Lab.R: -------------------------------------------------------------------------------- 1 | # Лабораторная работа 1 к главе 10: Анализ главных компонент 2 | 3 | states=row.names(USArrests) 4 | states 5 | names(USArrests) 6 | apply(USArrests, 2, mean) 7 | apply(USArrests, 2, var) 8 | pr.out=prcomp(USArrests, scale=TRUE) 9 | names(pr.out) 10 | pr.out$center 11 | pr.out$scale 12 | pr.out$rotation 13 | dim(pr.out$x) 14 | biplot(pr.out, scale=0) 15 | pr.out$rotation=-pr.out$rotation 16 | pr.out$x=-pr.out$x 17 | biplot(pr.out, scale=0) 18 | pr.out$sdev 19 | pr.var=pr.out$sdev^2 20 | pr.var 21 | pve=pr.var/sum(pr.var) 22 | pve 23 | plot(pve, xlab="Principal Component", ylab="Proportion of Variance Explained", ylim=c(0,1),type='b') 24 | plot(cumsum(pve), xlab="Principal Component", ylab="Cumulative Proportion of Variance Explained", ylim=c(0,1),type='b') 25 | a=c(1,2,8,-3) 26 | cumsum(a) 27 | 28 | 29 | # Лабораторная работа 2 к главе 10: Кластеризация 30 | 31 | # Кластеризация по методу К средних 32 | 33 | set.seed(2) 34 | x=matrix(rnorm(50*2), ncol=2) 35 | x[1:25,1]=x[1:25,1]+3 36 | x[1:25,2]=x[1:25,2]-4 37 | km.out=kmeans(x,2,nstart=20) 38 | km.out$cluster 39 | plot(x, col=(km.out$cluster+1), main="K-Means Clustering Results with K=2", xlab="", ylab="", pch=20, cex=2) 40 | set.seed(4) 41 | km.out=kmeans(x,3,nstart=20) 42 | km.out 43 | plot(x, col=(km.out$cluster+1), main="K-Means Clustering Results with K=3", xlab="", ylab="", pch=20, cex=2) 44 | set.seed(3) 45 | km.out=kmeans(x,3,nstart=1) 46 | km.out$tot.withinss 47 | km.out=kmeans(x,3,nstart=20) 48 | km.out$tot.withinss 49 | 50 | # Иерархическая кластеризация 51 | 52 | hc.complete=hclust(dist(x), method="complete") 53 | hc.average=hclust(dist(x), method="average") 54 | hc.single=hclust(dist(x), method="single") 55 | par(mfrow=c(1,3)) 56 | plot(hc.complete,main="Complete Linkage", xlab="", sub="", cex=.9) 57 | plot(hc.average, main="Average Linkage", xlab="", sub="", cex=.9) 58 | plot(hc.single, main="Single Linkage", xlab="", sub="", cex=.9) 59 | cutree(hc.complete, 2) 60 | cutree(hc.average, 2) 61 | cutree(hc.single, 2) 62 | cutree(hc.single, 4) 63 | xsc=scale(x) 64 | plot(hclust(dist(xsc), method="complete"), main="Hierarchical Clustering with Scaled Features") 65 | x=matrix(rnorm(30*3), ncol=3) 66 | dd=as.dist(1-cor(t(x))) 67 | plot(hclust(dd, method="complete"), main="Complete Linkage with Correlation-Based Distance", xlab="", sub="") 68 | 69 | 70 | # Лабораторная работа 3 к главе 10: Анализ данных NCI60 71 | 72 | # Данные NCI60 73 | 74 | library(ISLR) 75 | nci.labs=NCI60$labs 76 | nci.data=NCI60$data 77 | dim(nci.data) 78 | nci.labs[1:4] 79 | table(nci.labs) 80 | 81 | # PCA в приложении к данным NCI60 82 | 83 | pr.out=prcomp(nci.data, scale=TRUE) 84 | Cols=function(vec){ 85 | cols=rainbow(length(unique(vec))) 86 | return(cols[as.numeric(as.factor(vec))]) 87 | } 88 | par(mfrow=c(1,2)) 89 | plot(pr.out$x[,1:2], col=Cols(nci.labs), pch=19,xlab="Z1",ylab="Z2") 90 | plot(pr.out$x[,c(1,3)], col=Cols(nci.labs), pch=19,xlab="Z1",ylab="Z3") 91 | summary(pr.out) 92 | plot(pr.out) 93 | pve=100*pr.out$sdev^2/sum(pr.out$sdev^2) 94 | par(mfrow=c(1,2)) 95 | plot(pve, type="o", ylab="PVE", xlab="Principal Component", col="blue") 96 | plot(cumsum(pve), type="o", ylab="Cumulative PVE", xlab="Principal Component", col="brown3") 97 | 98 | # Кластеризация наблюдений из нобора данных NCI60 99 | 100 | sd.data=scale(nci.data) 101 | par(mfrow=c(1,3)) 102 | data.dist=dist(sd.data) 103 | plot(hclust(data.dist), labels=nci.labs, main="Complete Linkage", xlab="", sub="",ylab="") 104 | plot(hclust(data.dist, method="average"), labels=nci.labs, main="Average Linkage", xlab="", sub="",ylab="") 105 | plot(hclust(data.dist, method="single"), labels=nci.labs, main="Single Linkage", xlab="", sub="",ylab="") 106 | hc.out=hclust(dist(sd.data)) 107 | hc.clusters=cutree(hc.out,4) 108 | table(hc.clusters,nci.labs) 109 | par(mfrow=c(1,1)) 110 | plot(hc.out, labels=nci.labs) 111 | abline(h=139, col="red") 112 | hc.out 113 | set.seed(2) 114 | km.out=kmeans(sd.data, 4, nstart=20) 115 | km.clusters=km.out$cluster 116 | table(km.clusters,hc.clusters) 117 | hc.out=hclust(dist(pr.out$x[,1:5])) 118 | plot(hc.out, labels=nci.labs, main="Hier. Clust. on First Five Score Vectors") 119 | table(cutree(hc.out,4), nci.labs) 120 | 121 | -------------------------------------------------------------------------------- /Code/Chapter_2_Lab.R: -------------------------------------------------------------------------------- 1 | # Лабораторная работа к главе 2: Введение в R 2 | 3 | # Основные команды 4 | 5 | x <- c(1,3,2,5) 6 | x 7 | x = c(1,6,2) 8 | x 9 | y = c(1,4,3) 10 | length(x) 11 | length(y) 12 | x+y 13 | ls() 14 | rm(x,y) 15 | ls() 16 | rm(list=ls()) 17 | ?matrix 18 | x=matrix(data=c(1,2,3,4), nrow=2, ncol=2) 19 | x 20 | x=matrix(c(1,2,3,4),2,2) 21 | matrix(c(1,2,3,4),2,2,byrow=TRUE) 22 | sqrt(x) 23 | x^2 24 | x=rnorm(50) 25 | y=x+rnorm(50,mean=50,sd=.1) 26 | cor(x,y) 27 | set.seed(1303) 28 | rnorm(50) 29 | set.seed(3) 30 | y=rnorm(100) 31 | mean(y) 32 | var(y) 33 | sqrt(var(y)) 34 | sd(y) 35 | 36 | # Графики 37 | 38 | x=rnorm(100) 39 | y=rnorm(100) 40 | plot(x,y) 41 | plot(x,y,xlab="this is the x-axis",ylab="this is the y-axis",main="Plot of X vs Y") 42 | pdf("Figure.pdf") 43 | plot(x,y,col="green") 44 | dev.off() 45 | x=seq(1,10) 46 | x 47 | x=1:10 48 | x 49 | x=seq(-pi,pi,length=50) 50 | y=x 51 | f=outer(x,y,function(x,y)cos(y)/(1+x^2)) 52 | contour(x,y,f) 53 | contour(x,y,f,nlevels=45,add=T) 54 | fa=(f-t(f))/2 55 | contour(x,y,fa,nlevels=15) 56 | image(x,y,fa) 57 | persp(x,y,fa) 58 | persp(x,y,fa,theta=30) 59 | persp(x,y,fa,theta=30,phi=20) 60 | persp(x,y,fa,theta=30,phi=70) 61 | persp(x,y,fa,theta=30,phi=40) 62 | 63 | # Индексирование данных 64 | 65 | A=matrix(1:16,4,4) 66 | A 67 | A[2,3] 68 | A[c(1,3),c(2,4)] 69 | A[1:3,2:4] 70 | A[1:2,] 71 | A[,1:2] 72 | A[1,] 73 | A[-c(1,3),] 74 | A[-c(1,3),-c(1,3,4)] 75 | dim(A) 76 | 77 | # Загрузка данных 78 | 79 | Auto=read.table("Auto.data") 80 | fix(Auto) 81 | Auto=read.table("Auto.data",header=T,na.strings="?") 82 | fix(Auto) 83 | Auto=read.csv("Auto.csv",header=T,na.strings="?") 84 | fix(Auto) 85 | dim(Auto) 86 | Auto[1:4,] 87 | Auto=na.omit(Auto) 88 | dim(Auto) 89 | names(Auto) 90 | 91 | # Дополнительные количественные и графические сводки 92 | 93 | plot(cylinders, mpg) 94 | plot(Auto$cylinders, Auto$mpg) 95 | attach(Auto) 96 | plot(cylinders, mpg) 97 | cylinders=as.factor(cylinders) 98 | plot(cylinders, mpg) 99 | plot(cylinders, mpg, col="red") 100 | plot(cylinders, mpg, col="red", varwidth=T) 101 | plot(cylinders, mpg, col="red", varwidth=T,horizontal=T) 102 | plot(cylinders, mpg, col="red", varwidth=T, xlab="cylinders", ylab="MPG") 103 | hist(mpg) 104 | hist(mpg,col=2) 105 | hist(mpg,col=2,breaks=15) 106 | pairs(Auto) 107 | pairs(~ mpg + displacement + horsepower + weight + acceleration, Auto) 108 | plot(horsepower,mpg) 109 | identify(horsepower,mpg,name) 110 | summary(Auto) 111 | summary(mpg) 112 | -------------------------------------------------------------------------------- /Code/Chapter_3_Lab.R: -------------------------------------------------------------------------------- 1 | # Лабораторная работа к главе 3: Линейная регрессия 2 | 3 | library(MASS) 4 | library(ISLR) 5 | 6 | # Простая линейная регрессия 7 | 8 | fix(Boston) 9 | names(Boston) 10 | lm.fit=lm(medv~lstat) 11 | lm.fit=lm(medv~lstat,data=Boston) 12 | attach(Boston) 13 | lm.fit=lm(medv~lstat) 14 | lm.fit 15 | summary(lm.fit) 16 | names(lm.fit) 17 | coef(lm.fit) 18 | confint(lm.fit) 19 | predict(lm.fit,data.frame(lstat=(c(5,10,15))), interval="confidence") 20 | predict(lm.fit,data.frame(lstat=(c(5,10,15))), interval="prediction") 21 | plot(lstat,medv) 22 | abline(lm.fit) 23 | abline(lm.fit,lwd=3) 24 | abline(lm.fit,lwd=3,col="red") 25 | plot(lstat,medv,col="red") 26 | plot(lstat,medv,pch=20) 27 | plot(lstat,medv,pch="+") 28 | plot(1:20,1:20,pch=1:20) 29 | par(mfrow=c(2,2)) 30 | plot(lm.fit) 31 | plot(predict(lm.fit), residuals(lm.fit)) 32 | plot(predict(lm.fit), rstudent(lm.fit)) 33 | plot(hatvalues(lm.fit)) 34 | which.max(hatvalues(lm.fit)) 35 | 36 | # Множественная линейная регресси 37 | 38 | lm.fit=lm(medv~lstat+age,data=Boston) 39 | summary(lm.fit) 40 | lm.fit=lm(medv~.,data=Boston) 41 | summary(lm.fit) 42 | library(car) 43 | vif(lm.fit) 44 | lm.fit1=lm(medv~.-age,data=Boston) 45 | summary(lm.fit1) 46 | lm.fit1=update(lm.fit, ~.-age) 47 | 48 | # Эффекты взаимодействий 49 | 50 | summary(lm(medv~lstat*age,data=Boston)) 51 | 52 | # Нелинейные преобразования предикторов 53 | 54 | lm.fit2=lm(medv~lstat+I(lstat^2)) 55 | summary(lm.fit2) 56 | lm.fit=lm(medv~lstat) 57 | anova(lm.fit,lm.fit2) 58 | par(mfrow=c(2,2)) 59 | plot(lm.fit2) 60 | lm.fit5=lm(medv~poly(lstat,5)) 61 | summary(lm.fit5) 62 | summary(lm(medv~log(rm),data=Boston)) 63 | 64 | # Качественные предикторы 65 | 66 | fix(Carseats) 67 | names(Carseats) 68 | lm.fit=lm(Sales~.+Income:Advertising+Price:Age,data=Carseats) 69 | summary(lm.fit) 70 | attach(Carseats) 71 | contrasts(ShelveLoc) 72 | 73 | # Написание функций 74 | 75 | LoadLibraries 76 | LoadLibraries() 77 | LoadLibraries=function(){ 78 | library(ISLR) 79 | library(MASS) 80 | print("The libraries have been loaded.") 81 | } 82 | LoadLibraries 83 | LoadLibraries() 84 | -------------------------------------------------------------------------------- /Code/Chapter_4_Lab.R: -------------------------------------------------------------------------------- 1 | # Лабораторная работа к главе 4: Логистическая регрессия, LDA, QDA, и KNN 2 | 3 | # Данные по цене акций 4 | 5 | library(ISLR) 6 | names(Smarket) 7 | dim(Smarket) 8 | summary(Smarket) 9 | pairs(Smarket) 10 | cor(Smarket) 11 | cor(Smarket[,-9]) 12 | attach(Smarket) 13 | plot(Volume) 14 | 15 | # Логистическая регрессия 16 | 17 | glm.fit=glm(Direction~Lag1+Lag2+Lag3+Lag4+Lag5+Volume,data=Smarket,family=binomial) 18 | summary(glm.fit) 19 | coef(glm.fit) 20 | summary(glm.fit)$coef 21 | summary(glm.fit)$coef[,4] 22 | glm.probs=predict(glm.fit,type="response") 23 | glm.probs[1:10] 24 | contrasts(Direction) 25 | glm.pred=rep("Down",1250) 26 | glm.pred[glm.probs>.5]="Up" 27 | table(glm.pred,Direction) 28 | (507+145)/1250 29 | mean(glm.pred==Direction) 30 | train=(Year<2005) 31 | Smarket.2005=Smarket[!train,] 32 | dim(Smarket.2005) 33 | Direction.2005=Direction[!train] 34 | glm.fit=glm(Direction~Lag1+Lag2+Lag3+Lag4+Lag5+Volume,data=Smarket,family=binomial,subset=train) 35 | glm.probs=predict(glm.fit,Smarket.2005,type="response") 36 | glm.pred=rep("Down",252) 37 | glm.pred[glm.probs>.5]="Up" 38 | table(glm.pred,Direction.2005) 39 | mean(glm.pred==Direction.2005) 40 | mean(glm.pred!=Direction.2005) 41 | glm.fit=glm(Direction~Lag1+Lag2,data=Smarket,family=binomial,subset=train) 42 | glm.probs=predict(glm.fit,Smarket.2005,type="response") 43 | glm.pred=rep("Down",252) 44 | glm.pred[glm.probs>.5]="Up" 45 | table(glm.pred,Direction.2005) 46 | mean(glm.pred==Direction.2005) 47 | 106/(106+76) 48 | predict(glm.fit,newdata=data.frame(Lag1=c(1.2,1.5),Lag2=c(1.1,-0.8)),type="response") 49 | 50 | # Линейный дискриминантный анализ 51 | 52 | library(MASS) 53 | lda.fit=lda(Direction~Lag1+Lag2,data=Smarket,subset=train) 54 | lda.fit 55 | plot(lda.fit) 56 | lda.pred=predict(lda.fit, Smarket.2005) 57 | names(lda.pred) 58 | lda.class=lda.pred$class 59 | table(lda.class,Direction.2005) 60 | mean(lda.class==Direction.2005) 61 | sum(lda.pred$posterior[,1]>=.5) 62 | sum(lda.pred$posterior[,1]<.5) 63 | lda.pred$posterior[1:20,1] 64 | lda.class[1:20] 65 | sum(lda.pred$posterior[,1]>.9) 66 | 67 | # Квадратичный дискриминантный анализ 68 | 69 | qda.fit=qda(Direction~Lag1+Lag2,data=Smarket,subset=train) 70 | qda.fit 71 | qda.class=predict(qda.fit,Smarket.2005)$class 72 | table(qda.class,Direction.2005) 73 | mean(qda.class==Direction.2005) 74 | 75 | # Метод К ближайших соседей 76 | 77 | library(class) 78 | train.X=cbind(Lag1,Lag2)[train,] 79 | test.X=cbind(Lag1,Lag2)[!train,] 80 | train.Direction=Direction[train] 81 | set.seed(1) 82 | knn.pred=knn(train.X,test.X,train.Direction,k=1) 83 | table(knn.pred,Direction.2005) 84 | (83+43)/252 85 | knn.pred=knn(train.X,test.X,train.Direction,k=3) 86 | table(knn.pred,Direction.2005) 87 | mean(knn.pred==Direction.2005) 88 | 89 | # Анализ данных по жилым прицепам 90 | 91 | dim(Caravan) 92 | attach(Caravan) 93 | summary(Purchase) 94 | 348/5822 95 | standardized.X=scale(Caravan[,-86]) 96 | var(Caravan[,1]) 97 | var(Caravan[,2]) 98 | var(standardized.X[,1]) 99 | var(standardized.X[,2]) 100 | test=1:1000 101 | train.X=standardized.X[-test,] 102 | test.X=standardized.X[test,] 103 | train.Y=Purchase[-test] 104 | test.Y=Purchase[test] 105 | set.seed(1) 106 | knn.pred=knn(train.X,test.X,train.Y,k=1) 107 | mean(test.Y!=knn.pred) 108 | mean(test.Y!="No") 109 | table(knn.pred,test.Y) 110 | 9/(68+9) 111 | knn.pred=knn(train.X,test.X,train.Y,k=3) 112 | table(knn.pred,test.Y) 113 | 5/26 114 | knn.pred=knn(train.X,test.X,train.Y,k=5) 115 | table(knn.pred,test.Y) 116 | 4/15 117 | glm.fit=glm(Purchase~.,data=Caravan,family=binomial,subset=-test) 118 | glm.probs=predict(glm.fit,Caravan[test,],type="response") 119 | glm.pred=rep("No",1000) 120 | glm.pred[glm.probs>.5]="Yes" 121 | table(glm.pred,test.Y) 122 | glm.pred=rep("No",1000) 123 | glm.pred[glm.probs>.25]="Yes" 124 | table(glm.pred,test.Y) 125 | 11/(22+11) 126 | -------------------------------------------------------------------------------- /Code/Chapter_5_Lab.R: -------------------------------------------------------------------------------- 1 | # Лабораторная работа к главе 5: Перекрестная проверка и бутстреп 2 | 3 | # Метод проверочной выборки 4 | 5 | library(ISLR) 6 | set.seed(1) 7 | train=sample(392,196) 8 | lm.fit=lm(mpg~horsepower,data=Auto,subset=train) 9 | attach(Auto) 10 | mean((mpg-predict(lm.fit,Auto))[-train]^2) 11 | lm.fit2=lm(mpg~poly(horsepower,2),data=Auto,subset=train) 12 | mean((mpg-predict(lm.fit2,Auto))[-train]^2) 13 | lm.fit3=lm(mpg~poly(horsepower,3),data=Auto,subset=train) 14 | mean((mpg-predict(lm.fit3,Auto))[-train]^2) 15 | set.seed(2) 16 | train=sample(392,196) 17 | lm.fit=lm(mpg~horsepower,subset=train) 18 | mean((mpg-predict(lm.fit,Auto))[-train]^2) 19 | lm.fit2=lm(mpg~poly(horsepower,2),data=Auto,subset=train) 20 | mean((mpg-predict(lm.fit2,Auto))[-train]^2) 21 | lm.fit3=lm(mpg~poly(horsepower,3),data=Auto,subset=train) 22 | mean((mpg-predict(lm.fit3,Auto))[-train]^2) 23 | 24 | # Перекрестная проверка по отдельным наблюдениям 25 | 26 | glm.fit=glm(mpg~horsepower,data=Auto) 27 | coef(glm.fit) 28 | lm.fit=lm(mpg~horsepower,data=Auto) 29 | coef(lm.fit) 30 | library(boot) 31 | glm.fit=glm(mpg~horsepower,data=Auto) 32 | cv.err=cv.glm(Auto,glm.fit) 33 | cv.err$delta 34 | cv.error=rep(0,5) 35 | for (i in 1:5){ 36 | glm.fit=glm(mpg~poly(horsepower,i),data=Auto) 37 | cv.error[i]=cv.glm(Auto,glm.fit)$delta[1] 38 | } 39 | cv.error 40 | 41 | # k-кратная перекрестная проверка 42 | 43 | set.seed(17) 44 | cv.error.10=rep(0,10) 45 | for (i in 1:10){ 46 | glm.fit=glm(mpg~poly(horsepower,i),data=Auto) 47 | cv.error.10[i]=cv.glm(Auto,glm.fit,K=10)$delta[1] 48 | } 49 | cv.error.10 50 | 51 | # Бутстреп 52 | 53 | alpha.fn=function(data,index){ 54 | X=data$X[index] 55 | Y=data$Y[index] 56 | return((var(Y)-cov(X,Y))/(var(X)+var(Y)-2*cov(X,Y))) 57 | } 58 | alpha.fn(Portfolio,1:100) 59 | set.seed(1) 60 | alpha.fn(Portfolio,sample(100,100,replace=T)) 61 | boot(Portfolio,alpha.fn,R=1000) 62 | 63 | # Оценивание точности коэффициентов линейной регрессия 64 | 65 | boot.fn=function(data,index) 66 | return(coef(lm(mpg~horsepower,data=data,subset=index))) 67 | boot.fn(Auto,1:392) 68 | set.seed(1) 69 | boot.fn(Auto,sample(392,392,replace=T)) 70 | boot.fn(Auto,sample(392,392,replace=T)) 71 | boot(Auto,boot.fn,1000) 72 | summary(lm(mpg~horsepower,data=Auto))$coef 73 | boot.fn=function(data,index) 74 | coefficients(lm(mpg~horsepower+I(horsepower^2),data=data,subset=index)) 75 | set.seed(1) 76 | boot(Auto,boot.fn,1000) 77 | summary(lm(mpg~horsepower+I(horsepower^2),data=Auto))$coef 78 | 79 | -------------------------------------------------------------------------------- /Code/Chapter_6_Lab.R: -------------------------------------------------------------------------------- 1 | # Лабораторная работа 1 к главе 6: Методы отбора подмножеств переменных 2 | 3 | # Отбор оптимального подмножества 4 | 5 | library(ISLR) 6 | fix(Hitters) 7 | names(Hitters) 8 | dim(Hitters) 9 | sum(is.na(Hitters$Salary)) 10 | Hitters=na.omit(Hitters) 11 | dim(Hitters) 12 | sum(is.na(Hitters)) 13 | library(leaps) 14 | regfit.full=regsubsets(Salary~.,Hitters) 15 | summary(regfit.full) 16 | regfit.full=regsubsets(Salary~.,data=Hitters,nvmax=19) 17 | reg.summary=summary(regfit.full) 18 | names(reg.summary) 19 | reg.summary$rsq 20 | par(mfrow=c(2,2)) 21 | plot(reg.summary$rss,xlab="Number of Variables",ylab="RSS",type="l") 22 | plot(reg.summary$adjr2,xlab="Number of Variables",ylab="Adjusted RSq",type="l") 23 | which.max(reg.summary$adjr2) 24 | points(11,reg.summary$adjr2[11], col="red",cex=2,pch=20) 25 | plot(reg.summary$cp,xlab="Number of Variables",ylab="Cp",type='l') 26 | which.min(reg.summary$cp) 27 | points(10,reg.summary$cp[10],col="red",cex=2,pch=20) 28 | which.min(reg.summary$bic) 29 | plot(reg.summary$bic,xlab="Number of Variables",ylab="BIC",type='l') 30 | points(6,reg.summary$bic[6],col="red",cex=2,pch=20) 31 | plot(regfit.full,scale="r2") 32 | plot(regfit.full,scale="adjr2") 33 | plot(regfit.full,scale="Cp") 34 | plot(regfit.full,scale="bic") 35 | coef(regfit.full,6) 36 | 37 | # Пошаговые методы с добавлением и исключением переменных 38 | 39 | regfit.fwd=regsubsets(Salary~.,data=Hitters,nvmax=19,method="forward") 40 | summary(regfit.fwd) 41 | regfit.bwd=regsubsets(Salary~.,data=Hitters,nvmax=19,method="backward") 42 | summary(regfit.bwd) 43 | coef(regfit.full,7) 44 | coef(regfit.fwd,7) 45 | coef(regfit.bwd,7) 46 | 47 | # Выбор из нескольких моделей 48 | 49 | set.seed(1) 50 | train=sample(c(TRUE,FALSE), nrow(Hitters),rep=TRUE) 51 | test=(!train) 52 | regfit.best=regsubsets(Salary~.,data=Hitters[train,],nvmax=19) 53 | test.mat=model.matrix(Salary~.,data=Hitters[test,]) 54 | val.errors=rep(NA,19) 55 | for(i in 1:19){ 56 | coefi=coef(regfit.best,id=i) 57 | pred=test.mat[,names(coefi)]%*%coefi 58 | val.errors[i]=mean((Hitters$Salary[test]-pred)^2) 59 | } 60 | val.errors 61 | which.min(val.errors) 62 | coef(regfit.best,10) 63 | predict.regsubsets=function(object,newdata,id,...){ 64 | form=as.formula(object$call[[2]]) 65 | mat=model.matrix(form,newdata) 66 | coefi=coef(object,id=id) 67 | xvars=names(coefi) 68 | mat[,xvars]%*%coefi 69 | } 70 | regfit.best=regsubsets(Salary~.,data=Hitters,nvmax=19) 71 | coef(regfit.best,10) 72 | k=10 73 | set.seed(1) 74 | folds=sample(1:k,nrow(Hitters),replace=TRUE) 75 | cv.errors=matrix(NA,k,19, dimnames=list(NULL, paste(1:19))) 76 | for(j in 1:k){ 77 | best.fit=regsubsets(Salary~.,data=Hitters[folds!=j,],nvmax=19) 78 | for(i in 1:19){ 79 | pred=predict(best.fit,Hitters[folds==j,],id=i) 80 | cv.errors[j,i]=mean( (Hitters$Salary[folds==j]-pred)^2) 81 | } 82 | } 83 | mean.cv.errors=apply(cv.errors,2,mean) 84 | mean.cv.errors 85 | par(mfrow=c(1,1)) 86 | plot(mean.cv.errors,type='b') 87 | reg.best=regsubsets(Salary~.,data=Hitters, nvmax=19) 88 | coef(reg.best,11) 89 | 90 | 91 | # Лабораторная работа 2 к главе 6: Гребневая регрессия и лассо 92 | 93 | x=model.matrix(Salary~.,Hitters)[,-1] 94 | y=Hitters$Salary 95 | 96 | # Гребневая регрессия 97 | 98 | library(glmnet) 99 | grid=10^seq(10,-2,length=100) 100 | ridge.mod=glmnet(x,y,alpha=0,lambda=grid) 101 | dim(coef(ridge.mod)) 102 | ridge.mod$lambda[50] 103 | coef(ridge.mod)[,50] 104 | sqrt(sum(coef(ridge.mod)[-1,50]^2)) 105 | ridge.mod$lambda[60] 106 | coef(ridge.mod)[,60] 107 | sqrt(sum(coef(ridge.mod)[-1,60]^2)) 108 | predict(ridge.mod,s=50,type="coefficients")[1:20,] 109 | set.seed(1) 110 | train=sample(1:nrow(x), nrow(x)/2) 111 | test=(-train) 112 | y.test=y[test] 113 | ridge.mod=glmnet(x[train,],y[train],alpha=0,lambda=grid, thresh=1e-12) 114 | ridge.pred=predict(ridge.mod,s=4,newx=x[test,]) 115 | mean((ridge.pred-y.test)^2) 116 | mean((mean(y[train])-y.test)^2) 117 | ridge.pred=predict(ridge.mod,s=1e10,newx=x[test,]) 118 | mean((ridge.pred-y.test)^2) 119 | ridge.pred=predict(ridge.mod,s=0,newx=x[test,],exact=T) 120 | mean((ridge.pred-y.test)^2) 121 | lm(y~x, subset=train) 122 | predict(ridge.mod,s=0,exact=T,type="coefficients")[1:20,] 123 | set.seed(1) 124 | cv.out=cv.glmnet(x[train,],y[train],alpha=0) 125 | plot(cv.out) 126 | bestlam=cv.out$lambda.min 127 | bestlam 128 | ridge.pred=predict(ridge.mod,s=bestlam,newx=x[test,]) 129 | mean((ridge.pred-y.test)^2) 130 | out=glmnet(x,y,alpha=0) 131 | predict(out,type="coefficients",s=bestlam)[1:20,] 132 | 133 | # Лассо 134 | 135 | lasso.mod=glmnet(x[train,],y[train],alpha=1,lambda=grid) 136 | plot(lasso.mod) 137 | set.seed(1) 138 | cv.out=cv.glmnet(x[train,],y[train],alpha=1) 139 | plot(cv.out) 140 | bestlam=cv.out$lambda.min 141 | lasso.pred=predict(lasso.mod,s=bestlam,newx=x[test,]) 142 | mean((lasso.pred-y.test)^2) 143 | out=glmnet(x,y,alpha=1,lambda=grid) 144 | lasso.coef=predict(out,type="coefficients",s=bestlam)[1:20,] 145 | lasso.coef 146 | lasso.coef[lasso.coef!=0] 147 | 148 | 149 | # Лабораторная работа 3 к главе 6: PCR- и PLS-регрессия 150 | 151 | # Регрессия на главные компоненты 152 | 153 | library(pls) 154 | set.seed(2) 155 | pcr.fit=pcr(Salary~., data=Hitters,scale=TRUE,validation="CV") 156 | summary(pcr.fit) 157 | validationplot(pcr.fit,val.type="MSEP") 158 | set.seed(1) 159 | pcr.fit=pcr(Salary~., data=Hitters,subset=train,scale=TRUE, validation="CV") 160 | validationplot(pcr.fit,val.type="MSEP") 161 | pcr.pred=predict(pcr.fit,x[test,],ncomp=7) 162 | mean((pcr.pred-y.test)^2) 163 | pcr.fit=pcr(y~x,scale=TRUE,ncomp=7) 164 | summary(pcr.fit) 165 | 166 | # Частные наименьшие квадраты 167 | 168 | set.seed(1) 169 | pls.fit=plsr(Salary~., data=Hitters,subset=train,scale=TRUE, validation="CV") 170 | summary(pls.fit) 171 | validationplot(pls.fit,val.type="MSEP") 172 | pls.pred=predict(pls.fit,x[test,],ncomp=2) 173 | mean((pls.pred-y.test)^2) 174 | pls.fit=plsr(Salary~., data=Hitters,scale=TRUE,ncomp=2) 175 | summary(pls.fit) 176 | -------------------------------------------------------------------------------- /Code/Chapter_7_Lab.R: -------------------------------------------------------------------------------- 1 | # Лабораторная работа к главе 7: Нелинейные модели 2 | 3 | library(ISLR) 4 | attach(Wage) 5 | 6 | # Полиномиальная регрессия и ступенчатые функции 7 | 8 | fit=lm(wage~poly(age,4),data=Wage) 9 | coef(summary(fit)) 10 | fit2=lm(wage~poly(age,4,raw=T),data=Wage) 11 | coef(summary(fit2)) 12 | fit2a=lm(wage~age+I(age^2)+I(age^3)+I(age^4),data=Wage) 13 | coef(fit2a) 14 | fit2b=lm(wage~cbind(age,age^2,age^3,age^4),data=Wage) 15 | agelims=range(age) 16 | age.grid=seq(from=agelims[1],to=agelims[2]) 17 | preds=predict(fit,newdata=list(age=age.grid),se=TRUE) 18 | se.bands=cbind(preds$fit+2*preds$se.fit,preds$fit-2*preds$se.fit) 19 | par(mfrow=c(1,2),mar=c(4.5,4.5,1,1),oma=c(0,0,4,0)) 20 | plot(age,wage,xlim=agelims,cex=.5,col="darkgrey") 21 | title("Degree-4 Polynomial",outer=T) 22 | lines(age.grid,preds$fit,lwd=2,col="blue") 23 | matlines(age.grid,se.bands,lwd=1,col="blue",lty=3) 24 | preds2=predict(fit2,newdata=list(age=age.grid),se=TRUE) 25 | max(abs(preds$fit-preds2$fit)) 26 | fit.1=lm(wage~age,data=Wage) 27 | fit.2=lm(wage~poly(age,2),data=Wage) 28 | fit.3=lm(wage~poly(age,3),data=Wage) 29 | fit.4=lm(wage~poly(age,4),data=Wage) 30 | fit.5=lm(wage~poly(age,5),data=Wage) 31 | anova(fit.1,fit.2,fit.3,fit.4,fit.5) 32 | coef(summary(fit.5)) 33 | (-11.983)^2 34 | fit.1=lm(wage~education+age,data=Wage) 35 | fit.2=lm(wage~education+poly(age,2),data=Wage) 36 | fit.3=lm(wage~education+poly(age,3),data=Wage) 37 | anova(fit.1,fit.2,fit.3) 38 | fit=glm(I(wage>250)~poly(age,4),data=Wage,family=binomial) 39 | preds=predict(fit,newdata=list(age=age.grid),se=T) 40 | pfit=exp(preds$fit)/(1+exp(preds$fit)) 41 | se.bands.logit = cbind(preds$fit+2*preds$se.fit, preds$fit-2*preds$se.fit) 42 | se.bands = exp(se.bands.logit)/(1+exp(se.bands.logit)) 43 | preds=predict(fit,newdata=list(age=age.grid),type="response",se=T) 44 | plot(age,I(wage>250),xlim=agelims,type="n",ylim=c(0,.2)) 45 | points(jitter(age), I((wage>250)/5),cex=.5,pch="|",col="darkgrey") 46 | lines(age.grid,pfit,lwd=2, col="blue") 47 | matlines(age.grid,se.bands,lwd=1,col="blue",lty=3) 48 | table(cut(age,4)) 49 | fit=lm(wage~cut(age,4),data=Wage) 50 | coef(summary(fit)) 51 | 52 | # Сплайны 53 | 54 | library(splines) 55 | fit=lm(wage~bs(age,knots=c(25,40,60)),data=Wage) 56 | pred=predict(fit,newdata=list(age=age.grid),se=T) 57 | plot(age,wage,col="gray") 58 | lines(age.grid,pred$fit,lwd=2) 59 | lines(age.grid,pred$fit+2*pred$se,lty="dashed") 60 | lines(age.grid,pred$fit-2*pred$se,lty="dashed") 61 | dim(bs(age,knots=c(25,40,60))) 62 | dim(bs(age,df=6)) 63 | attr(bs(age,df=6),"knots") 64 | fit2=lm(wage~ns(age,df=4),data=Wage) 65 | pred2=predict(fit2,newdata=list(age=age.grid),se=T) 66 | lines(age.grid, pred2$fit,col="red",lwd=2) 67 | plot(age,wage,xlim=agelims,cex=.5,col="darkgrey") 68 | title("Smoothing Spline") 69 | fit=smooth.spline(age,wage,df=16) 70 | fit2=smooth.spline(age,wage,cv=TRUE) 71 | fit2$df 72 | lines(fit,col="red",lwd=2) 73 | lines(fit2,col="blue",lwd=2) 74 | legend("topright",legend=c("16 DF","6.8 DF"),col=c("red","blue"),lty=1,lwd=2,cex=.8) 75 | plot(age,wage,xlim=agelims,cex=.5,col="darkgrey") 76 | title("Local Regression") 77 | fit=loess(wage~age,span=.2,data=Wage) 78 | fit2=loess(wage~age,span=.5,data=Wage) 79 | lines(age.grid,predict(fit,data.frame(age=age.grid)),col="red",lwd=2) 80 | lines(age.grid,predict(fit2,data.frame(age=age.grid)),col="blue",lwd=2) 81 | legend("topright",legend=c("Span=0.2","Span=0.5"),col=c("red","blue"),lty=1,lwd=2,cex=.8) 82 | 83 | # GAM 84 | 85 | gam1=lm(wage~ns(year,4)+ns(age,5)+education,data=Wage) 86 | library(gam) 87 | gam.m3=gam(wage~s(year,4)+s(age,5)+education,data=Wage) 88 | par(mfrow=c(1,3)) 89 | plot(gam.m3, se=TRUE,col="blue") 90 | plot.gam(gam1, se=TRUE, col="red") 91 | gam.m1=gam(wage~s(age,5)+education,data=Wage) 92 | gam.m2=gam(wage~year+s(age,5)+education,data=Wage) 93 | anova(gam.m1,gam.m2,gam.m3,test="F") 94 | summary(gam.m3) 95 | preds=predict(gam.m2,newdata=Wage) 96 | gam.lo=gam(wage~s(year,df=4)+lo(age,span=0.7)+education,data=Wage) 97 | plot.gam(gam.lo, se=TRUE, col="green") 98 | gam.lo.i=gam(wage~lo(year,age,span=0.5)+education,data=Wage) 99 | library(akima) 100 | plot(gam.lo.i) 101 | gam.lr=gam(I(wage>250)~year+s(age,df=5)+education,family=binomial,data=Wage) 102 | par(mfrow=c(1,3)) 103 | plot(gam.lr,se=T,col="green") 104 | table(education,I(wage>250)) 105 | gam.lr.s=gam(I(wage>250)~year+s(age,df=5)+education,family=binomial,data=Wage,subset=(education!="1. < HS Grad")) 106 | plot(gam.lr.s,se=T,col="green") 107 | 108 | -------------------------------------------------------------------------------- /Code/Chapter_8_Lab.R: -------------------------------------------------------------------------------- 1 | # Лабораторная работа к главе 8: Деревья решений 2 | 3 | # Деревья классификации 4 | 5 | library(tree) 6 | library(ISLR) 7 | attach(Carseats) 8 | High=ifelse(Sales<=8,"No","Yes") 9 | Carseats=data.frame(Carseats,High) 10 | tree.carseats=tree(High~.-Sales,Carseats) 11 | summary(tree.carseats) 12 | plot(tree.carseats) 13 | text(tree.carseats,pretty=0) 14 | tree.carseats 15 | set.seed(2) 16 | train=sample(1:nrow(Carseats), 200) 17 | Carseats.test=Carseats[-train,] 18 | High.test=High[-train] 19 | tree.carseats=tree(High~.-Sales,Carseats,subset=train) 20 | tree.pred=predict(tree.carseats,Carseats.test,type="class") 21 | table(tree.pred,High.test) 22 | (86+57)/200 23 | set.seed(3) 24 | cv.carseats=cv.tree(tree.carseats,FUN=prune.misclass) 25 | names(cv.carseats) 26 | cv.carseats 27 | par(mfrow=c(1,2)) 28 | plot(cv.carseats$size,cv.carseats$dev,type="b") 29 | plot(cv.carseats$k,cv.carseats$dev,type="b") 30 | prune.carseats=prune.misclass(tree.carseats,best=9) 31 | plot(prune.carseats) 32 | text(prune.carseats,pretty=0) 33 | tree.pred=predict(prune.carseats,Carseats.test,type="class") 34 | table(tree.pred,High.test) 35 | (94+60)/200 36 | prune.carseats=prune.misclass(tree.carseats,best=15) 37 | plot(prune.carseats) 38 | text(prune.carseats,pretty=0) 39 | tree.pred=predict(prune.carseats,Carseats.test,type="class") 40 | table(tree.pred,High.test) 41 | (86+62)/200 42 | 43 | # Регрессионные деревья 44 | 45 | library(MASS) 46 | set.seed(1) 47 | train = sample(1:nrow(Boston), nrow(Boston)/2) 48 | tree.boston=tree(medv~.,Boston,subset=train) 49 | summary(tree.boston) 50 | plot(tree.boston) 51 | text(tree.boston,pretty=0) 52 | cv.boston=cv.tree(tree.boston) 53 | plot(cv.boston$size,cv.boston$dev,type='b') 54 | prune.boston=prune.tree(tree.boston,best=5) 55 | plot(prune.boston) 56 | text(prune.boston,pretty=0) 57 | yhat=predict(tree.boston,newdata=Boston[-train,]) 58 | boston.test=Boston[-train,"medv"] 59 | plot(yhat,boston.test) 60 | abline(0,1) 61 | mean((yhat-boston.test)^2) 62 | 63 | # Бэггинг и метод случайного леса 64 | 65 | library(randomForest) 66 | set.seed(1) 67 | bag.boston=randomForest(medv~.,data=Boston,subset=train,mtry=13,importance=TRUE) 68 | bag.boston 69 | yhat.bag = predict(bag.boston,newdata=Boston[-train,]) 70 | plot(yhat.bag, boston.test) 71 | abline(0,1) 72 | mean((yhat.bag-boston.test)^2) 73 | bag.boston=randomForest(medv~.,data=Boston,subset=train,mtry=13,ntree=25) 74 | yhat.bag = predict(bag.boston,newdata=Boston[-train,]) 75 | mean((yhat.bag-boston.test)^2) 76 | set.seed(1) 77 | rf.boston=randomForest(medv~.,data=Boston,subset=train,mtry=6,importance=TRUE) 78 | yhat.rf = predict(rf.boston,newdata=Boston[-train,]) 79 | mean((yhat.rf-boston.test)^2) 80 | importance(rf.boston) 81 | varImpPlot(rf.boston) 82 | 83 | # Бустинг 84 | 85 | library(gbm) 86 | set.seed(1) 87 | boost.boston=gbm(medv~.,data=Boston[train,],distribution="gaussian",n.trees=5000,interaction.depth=4) 88 | summary(boost.boston) 89 | par(mfrow=c(1,2)) 90 | plot(boost.boston,i="rm") 91 | plot(boost.boston,i="lstat") 92 | yhat.boost=predict(boost.boston,newdata=Boston[-train,],n.trees=5000) 93 | mean((yhat.boost-boston.test)^2) 94 | boost.boston=gbm(medv~.,data=Boston[train,],distribution="gaussian",n.trees=5000,interaction.depth=4,shrinkage=0.2,verbose=F) 95 | yhat.boost=predict(boost.boston,newdata=Boston[-train,],n.trees=5000) 96 | mean((yhat.boost-boston.test)^2) 97 | 98 | -------------------------------------------------------------------------------- /Code/Chapter_9_Lab.R: -------------------------------------------------------------------------------- 1 | # Лабораторная работа к главе 9: Машины опорных векторов 2 | 3 | # Классификатор на опорных векторах 4 | 5 | set.seed(1) 6 | x=matrix(rnorm(20*2), ncol=2) 7 | y=c(rep(-1,10), rep(1,10)) 8 | x[y==1,]=x[y==1,] + 1 9 | plot(x, col=(3-y)) 10 | dat=data.frame(x=x, y=as.factor(y)) 11 | library(e1071) 12 | svmfit=svm(y~., data=dat, kernel="linear", cost=10,scale=FALSE) 13 | plot(svmfit, dat) 14 | svmfit$index 15 | summary(svmfit) 16 | svmfit=svm(y~., data=dat, kernel="linear", cost=0.1,scale=FALSE) 17 | plot(svmfit, dat) 18 | svmfit$index 19 | set.seed(1) 20 | tune.out=tune(svm,y~.,data=dat,kernel="linear",ranges=list(cost=c(0.001, 0.01, 0.1, 1,5,10,100))) 21 | summary(tune.out) 22 | bestmod=tune.out$best.model 23 | summary(bestmod) 24 | xtest=matrix(rnorm(20*2), ncol=2) 25 | ytest=sample(c(-1,1), 20, rep=TRUE) 26 | xtest[ytest==1,]=xtest[ytest==1,] + 1 27 | testdat=data.frame(x=xtest, y=as.factor(ytest)) 28 | ypred=predict(bestmod,testdat) 29 | table(predict=ypred, truth=testdat$y) 30 | svmfit=svm(y~., data=dat, kernel="linear", cost=.01,scale=FALSE) 31 | ypred=predict(svmfit,testdat) 32 | table(predict=ypred, truth=testdat$y) 33 | x[y==1,]=x[y==1,]+0.5 34 | plot(x, col=(y+5)/2, pch=19) 35 | dat=data.frame(x=x,y=as.factor(y)) 36 | svmfit=svm(y~., data=dat, kernel="linear", cost=1e5) 37 | summary(svmfit) 38 | plot(svmfit, dat) 39 | svmfit=svm(y~., data=dat, kernel="linear", cost=1) 40 | summary(svmfit) 41 | plot(svmfit,dat) 42 | 43 | # Машина опорных векторов 44 | 45 | set.seed(1) 46 | x=matrix(rnorm(200*2), ncol=2) 47 | x[1:100,]=x[1:100,]+2 48 | x[101:150,]=x[101:150,]-2 49 | y=c(rep(1,150),rep(2,50)) 50 | dat=data.frame(x=x,y=as.factor(y)) 51 | plot(x, col=y) 52 | train=sample(200,100) 53 | svmfit=svm(y~., data=dat[train,], kernel="radial", gamma=1, cost=1) 54 | plot(svmfit, dat[train,]) 55 | summary(svmfit) 56 | svmfit=svm(y~., data=dat[train,], kernel="radial",gamma=1,cost=1e5) 57 | plot(svmfit,dat[train,]) 58 | set.seed(1) 59 | tune.out=tune(svm, y~., data=dat[train,], kernel="radial", ranges=list(cost=c(0.1,1,10,100,1000),gamma=c(0.5,1,2,3,4))) 60 | summary(tune.out) 61 | table(true=dat[-train,"y"], pred=predict(tune.out$best.model,newdata=dat[-train,])) 62 | 63 | # ROC-кривые 64 | 65 | library(ROCR) 66 | rocplot=function(pred, truth, ...){ 67 | predob = prediction(pred, truth) 68 | perf = performance(predob, "tpr", "fpr") 69 | plot(perf,...)} 70 | svmfit.opt=svm(y~., data=dat[train,], kernel="radial",gamma=2, cost=1,decision.values=T) 71 | fitted=attributes(predict(svmfit.opt,dat[train,],decision.values=TRUE))$decision.values 72 | par(mfrow=c(1,2)) 73 | rocplot(fitted,dat[train,"y"],main="Training Data") 74 | svmfit.flex=svm(y~., data=dat[train,], kernel="radial",gamma=50, cost=1, decision.values=T) 75 | fitted=attributes(predict(svmfit.flex,dat[train,],decision.values=T))$decision.values 76 | rocplot(fitted,dat[train,"y"],add=T,col="red") 77 | fitted=attributes(predict(svmfit.opt,dat[-train,],decision.values=T))$decision.values 78 | rocplot(fitted,dat[-train,"y"],main="Test Data") 79 | fitted=attributes(predict(svmfit.flex,dat[-train,],decision.values=T))$decision.values 80 | rocplot(fitted,dat[-train,"y"],add=T,col="red") 81 | 82 | # SVM с несколькими классами 83 | 84 | set.seed(1) 85 | x=rbind(x, matrix(rnorm(50*2), ncol=2)) 86 | y=c(y, rep(0,50)) 87 | x[y==0,2]=x[y==0,2]+2 88 | dat=data.frame(x=x, y=as.factor(y)) 89 | par(mfrow=c(1,1)) 90 | plot(x,col=(y+1)) 91 | svmfit=svm(y~., data=dat, kernel="radial", cost=10, gamma=1) 92 | plot(svmfit, dat) 93 | 94 | # Анализ данных по уровню экспрессии генов 95 | 96 | library(ISLR) 97 | names(Khan) 98 | dim(Khan$xtrain) 99 | dim(Khan$xtest) 100 | length(Khan$ytrain) 101 | length(Khan$ytest) 102 | table(Khan$ytrain) 103 | table(Khan$ytest) 104 | dat=data.frame(x=Khan$xtrain, y=as.factor(Khan$ytrain)) 105 | out=svm(y~., data=dat, kernel="linear",cost=10) 106 | summary(out) 107 | table(out$fitted, dat$y) 108 | dat.te=data.frame(x=Khan$xtest, y=as.factor(Khan$ytest)) 109 | pred.te=predict(out, newdata=dat.te) 110 | table(pred.te, dat.te$y) 111 | 112 | -------------------------------------------------------------------------------- /Data/Advertising.csv: -------------------------------------------------------------------------------- 1 | "","TV","Radio","Newspaper","Sales" 2 | "1",230.1,37.8,69.2,22.1 3 | "2",44.5,39.3,45.1,10.4 4 | "3",17.2,45.9,69.3,9.3 5 | "4",151.5,41.3,58.5,18.5 6 | "5",180.8,10.8,58.4,12.9 7 | "6",8.7,48.9,75,7.2 8 | "7",57.5,32.8,23.5,11.8 9 | "8",120.2,19.6,11.6,13.2 10 | "9",8.6,2.1,1,4.8 11 | "10",199.8,2.6,21.2,10.6 12 | "11",66.1,5.8,24.2,8.6 13 | "12",214.7,24,4,17.4 14 | "13",23.8,35.1,65.9,9.2 15 | "14",97.5,7.6,7.2,9.7 16 | "15",204.1,32.9,46,19 17 | "16",195.4,47.7,52.9,22.4 18 | "17",67.8,36.6,114,12.5 19 | "18",281.4,39.6,55.8,24.4 20 | "19",69.2,20.5,18.3,11.3 21 | "20",147.3,23.9,19.1,14.6 22 | "21",218.4,27.7,53.4,18 23 | "22",237.4,5.1,23.5,12.5 24 | "23",13.2,15.9,49.6,5.6 25 | "24",228.3,16.9,26.2,15.5 26 | "25",62.3,12.6,18.3,9.7 27 | "26",262.9,3.5,19.5,12 28 | "27",142.9,29.3,12.6,15 29 | "28",240.1,16.7,22.9,15.9 30 | "29",248.8,27.1,22.9,18.9 31 | "30",70.6,16,40.8,10.5 32 | "31",292.9,28.3,43.2,21.4 33 | "32",112.9,17.4,38.6,11.9 34 | "33",97.2,1.5,30,9.6 35 | "34",265.6,20,0.3,17.4 36 | "35",95.7,1.4,7.4,9.5 37 | "36",290.7,4.1,8.5,12.8 38 | "37",266.9,43.8,5,25.4 39 | "38",74.7,49.4,45.7,14.7 40 | "39",43.1,26.7,35.1,10.1 41 | "40",228,37.7,32,21.5 42 | "41",202.5,22.3,31.6,16.6 43 | "42",177,33.4,38.7,17.1 44 | "43",293.6,27.7,1.8,20.7 45 | "44",206.9,8.4,26.4,12.9 46 | "45",25.1,25.7,43.3,8.5 47 | "46",175.1,22.5,31.5,14.9 48 | "47",89.7,9.9,35.7,10.6 49 | "48",239.9,41.5,18.5,23.2 50 | "49",227.2,15.8,49.9,14.8 51 | "50",66.9,11.7,36.8,9.7 52 | "51",199.8,3.1,34.6,11.4 53 | "52",100.4,9.6,3.6,10.7 54 | "53",216.4,41.7,39.6,22.6 55 | "54",182.6,46.2,58.7,21.2 56 | "55",262.7,28.8,15.9,20.2 57 | "56",198.9,49.4,60,23.7 58 | "57",7.3,28.1,41.4,5.5 59 | "58",136.2,19.2,16.6,13.2 60 | "59",210.8,49.6,37.7,23.8 61 | "60",210.7,29.5,9.3,18.4 62 | "61",53.5,2,21.4,8.1 63 | "62",261.3,42.7,54.7,24.2 64 | "63",239.3,15.5,27.3,15.7 65 | "64",102.7,29.6,8.4,14 66 | "65",131.1,42.8,28.9,18 67 | "66",69,9.3,0.9,9.3 68 | "67",31.5,24.6,2.2,9.5 69 | "68",139.3,14.5,10.2,13.4 70 | "69",237.4,27.5,11,18.9 71 | "70",216.8,43.9,27.2,22.3 72 | "71",199.1,30.6,38.7,18.3 73 | "72",109.8,14.3,31.7,12.4 74 | "73",26.8,33,19.3,8.8 75 | "74",129.4,5.7,31.3,11 76 | "75",213.4,24.6,13.1,17 77 | "76",16.9,43.7,89.4,8.7 78 | "77",27.5,1.6,20.7,6.9 79 | "78",120.5,28.5,14.2,14.2 80 | "79",5.4,29.9,9.4,5.3 81 | "80",116,7.7,23.1,11 82 | "81",76.4,26.7,22.3,11.8 83 | "82",239.8,4.1,36.9,12.3 84 | "83",75.3,20.3,32.5,11.3 85 | "84",68.4,44.5,35.6,13.6 86 | "85",213.5,43,33.8,21.7 87 | "86",193.2,18.4,65.7,15.2 88 | "87",76.3,27.5,16,12 89 | "88",110.7,40.6,63.2,16 90 | "89",88.3,25.5,73.4,12.9 91 | "90",109.8,47.8,51.4,16.7 92 | "91",134.3,4.9,9.3,11.2 93 | "92",28.6,1.5,33,7.3 94 | "93",217.7,33.5,59,19.4 95 | "94",250.9,36.5,72.3,22.2 96 | "95",107.4,14,10.9,11.5 97 | "96",163.3,31.6,52.9,16.9 98 | "97",197.6,3.5,5.9,11.7 99 | "98",184.9,21,22,15.5 100 | "99",289.7,42.3,51.2,25.4 101 | "100",135.2,41.7,45.9,17.2 102 | "101",222.4,4.3,49.8,11.7 103 | "102",296.4,36.3,100.9,23.8 104 | "103",280.2,10.1,21.4,14.8 105 | "104",187.9,17.2,17.9,14.7 106 | "105",238.2,34.3,5.3,20.7 107 | "106",137.9,46.4,59,19.2 108 | "107",25,11,29.7,7.2 109 | "108",90.4,0.3,23.2,8.7 110 | "109",13.1,0.4,25.6,5.3 111 | "110",255.4,26.9,5.5,19.8 112 | "111",225.8,8.2,56.5,13.4 113 | "112",241.7,38,23.2,21.8 114 | "113",175.7,15.4,2.4,14.1 115 | "114",209.6,20.6,10.7,15.9 116 | "115",78.2,46.8,34.5,14.6 117 | "116",75.1,35,52.7,12.6 118 | "117",139.2,14.3,25.6,12.2 119 | "118",76.4,0.8,14.8,9.4 120 | "119",125.7,36.9,79.2,15.9 121 | "120",19.4,16,22.3,6.6 122 | "121",141.3,26.8,46.2,15.5 123 | "122",18.8,21.7,50.4,7 124 | "123",224,2.4,15.6,11.6 125 | "124",123.1,34.6,12.4,15.2 126 | "125",229.5,32.3,74.2,19.7 127 | "126",87.2,11.8,25.9,10.6 128 | "127",7.8,38.9,50.6,6.6 129 | "128",80.2,0,9.2,8.8 130 | "129",220.3,49,3.2,24.7 131 | "130",59.6,12,43.1,9.7 132 | "131",0.7,39.6,8.7,1.6 133 | "132",265.2,2.9,43,12.7 134 | "133",8.4,27.2,2.1,5.7 135 | "134",219.8,33.5,45.1,19.6 136 | "135",36.9,38.6,65.6,10.8 137 | "136",48.3,47,8.5,11.6 138 | "137",25.6,39,9.3,9.5 139 | "138",273.7,28.9,59.7,20.8 140 | "139",43,25.9,20.5,9.6 141 | "140",184.9,43.9,1.7,20.7 142 | "141",73.4,17,12.9,10.9 143 | "142",193.7,35.4,75.6,19.2 144 | "143",220.5,33.2,37.9,20.1 145 | "144",104.6,5.7,34.4,10.4 146 | "145",96.2,14.8,38.9,11.4 147 | "146",140.3,1.9,9,10.3 148 | "147",240.1,7.3,8.7,13.2 149 | "148",243.2,49,44.3,25.4 150 | "149",38,40.3,11.9,10.9 151 | "150",44.7,25.8,20.6,10.1 152 | "151",280.7,13.9,37,16.1 153 | "152",121,8.4,48.7,11.6 154 | "153",197.6,23.3,14.2,16.6 155 | "154",171.3,39.7,37.7,19 156 | "155",187.8,21.1,9.5,15.6 157 | "156",4.1,11.6,5.7,3.2 158 | "157",93.9,43.5,50.5,15.3 159 | "158",149.8,1.3,24.3,10.1 160 | "159",11.7,36.9,45.2,7.3 161 | "160",131.7,18.4,34.6,12.9 162 | "161",172.5,18.1,30.7,14.4 163 | "162",85.7,35.8,49.3,13.3 164 | "163",188.4,18.1,25.6,14.9 165 | "164",163.5,36.8,7.4,18 166 | "165",117.2,14.7,5.4,11.9 167 | "166",234.5,3.4,84.8,11.9 168 | "167",17.9,37.6,21.6,8 169 | "168",206.8,5.2,19.4,12.2 170 | "169",215.4,23.6,57.6,17.1 171 | "170",284.3,10.6,6.4,15 172 | "171",50,11.6,18.4,8.4 173 | "172",164.5,20.9,47.4,14.5 174 | "173",19.6,20.1,17,7.6 175 | "174",168.4,7.1,12.8,11.7 176 | "175",222.4,3.4,13.1,11.5 177 | "176",276.9,48.9,41.8,27 178 | "177",248.4,30.2,20.3,20.2 179 | "178",170.2,7.8,35.2,11.7 180 | "179",276.7,2.3,23.7,11.8 181 | "180",165.6,10,17.6,12.6 182 | "181",156.6,2.6,8.3,10.5 183 | "182",218.5,5.4,27.4,12.2 184 | "183",56.2,5.7,29.7,8.7 185 | "184",287.6,43,71.8,26.2 186 | "185",253.8,21.3,30,17.6 187 | "186",205,45.1,19.6,22.6 188 | "187",139.5,2.1,26.6,10.3 189 | "188",191.1,28.7,18.2,17.3 190 | "189",286,13.9,3.7,15.9 191 | "190",18.7,12.1,23.4,6.7 192 | "191",39.5,41.1,5.8,10.8 193 | "192",75.5,10.8,6,9.9 194 | "193",17.2,4.1,31.6,5.9 195 | "194",166.8,42,3.6,19.6 196 | "195",149.7,35.6,6,17.3 197 | "196",38.2,3.7,13.8,7.6 198 | "197",94.2,4.9,8.1,9.7 199 | "198",177,9.3,6.4,12.8 200 | "199",283.6,42,66.2,25.5 201 | "200",232.1,8.6,8.7,13.4 202 | -------------------------------------------------------------------------------- /Data/Auto.csv: -------------------------------------------------------------------------------- 1 | mpg,cylinders,displacement,horsepower,weight,acceleration,year,origin,name 2 | 18,8,307,130,3504,12,70,1,chevrolet chevelle malibu 3 | 15,8,350,165,3693,11.5,70,1,buick skylark 320 4 | 18,8,318,150,3436,11,70,1,plymouth satellite 5 | 16,8,304,150,3433,12,70,1,amc rebel sst 6 | 17,8,302,140,3449,10.5,70,1,ford torino 7 | 15,8,429,198,4341,10,70,1,ford galaxie 500 8 | 14,8,454,220,4354,9,70,1,chevrolet impala 9 | 14,8,440,215,4312,8.5,70,1,plymouth fury iii 10 | 14,8,455,225,4425,10,70,1,pontiac catalina 11 | 15,8,390,190,3850,8.5,70,1,amc ambassador dpl 12 | 15,8,383,170,3563,10,70,1,dodge challenger se 13 | 14,8,340,160,3609,8,70,1,plymouth 'cuda 340 14 | 15,8,400,150,3761,9.5,70,1,chevrolet monte carlo 15 | 14,8,455,225,3086,10,70,1,buick estate wagon (sw) 16 | 24,4,113,95,2372,15,70,3,toyota corona mark ii 17 | 22,6,198,95,2833,15.5,70,1,plymouth duster 18 | 18,6,199,97,2774,15.5,70,1,amc hornet 19 | 21,6,200,85,2587,16,70,1,ford maverick 20 | 27,4,97,88,2130,14.5,70,3,datsun pl510 21 | 26,4,97,46,1835,20.5,70,2,volkswagen 1131 deluxe sedan 22 | 25,4,110,87,2672,17.5,70,2,peugeot 504 23 | 24,4,107,90,2430,14.5,70,2,audi 100 ls 24 | 25,4,104,95,2375,17.5,70,2,saab 99e 25 | 26,4,121,113,2234,12.5,70,2,bmw 2002 26 | 21,6,199,90,2648,15,70,1,amc gremlin 27 | 10,8,360,215,4615,14,70,1,ford f250 28 | 10,8,307,200,4376,15,70,1,chevy c20 29 | 11,8,318,210,4382,13.5,70,1,dodge d200 30 | 9,8,304,193,4732,18.5,70,1,hi 1200d 31 | 27,4,97,88,2130,14.5,71,3,datsun pl510 32 | 28,4,140,90,2264,15.5,71,1,chevrolet vega 2300 33 | 25,4,113,95,2228,14,71,3,toyota corona 34 | 25,4,98,?,2046,19,71,1,ford pinto 35 | 19,6,232,100,2634,13,71,1,amc gremlin 36 | 16,6,225,105,3439,15.5,71,1,plymouth satellite custom 37 | 17,6,250,100,3329,15.5,71,1,chevrolet chevelle malibu 38 | 19,6,250,88,3302,15.5,71,1,ford torino 500 39 | 18,6,232,100,3288,15.5,71,1,amc matador 40 | 14,8,350,165,4209,12,71,1,chevrolet impala 41 | 14,8,400,175,4464,11.5,71,1,pontiac catalina brougham 42 | 14,8,351,153,4154,13.5,71,1,ford galaxie 500 43 | 14,8,318,150,4096,13,71,1,plymouth fury iii 44 | 12,8,383,180,4955,11.5,71,1,dodge monaco (sw) 45 | 13,8,400,170,4746,12,71,1,ford country squire (sw) 46 | 13,8,400,175,5140,12,71,1,pontiac safari (sw) 47 | 18,6,258,110,2962,13.5,71,1,amc hornet sportabout (sw) 48 | 22,4,140,72,2408,19,71,1,chevrolet vega (sw) 49 | 19,6,250,100,3282,15,71,1,pontiac firebird 50 | 18,6,250,88,3139,14.5,71,1,ford mustang 51 | 23,4,122,86,2220,14,71,1,mercury capri 2000 52 | 28,4,116,90,2123,14,71,2,opel 1900 53 | 30,4,79,70,2074,19.5,71,2,peugeot 304 54 | 30,4,88,76,2065,14.5,71,2,fiat 124b 55 | 31,4,71,65,1773,19,71,3,toyota corolla 1200 56 | 35,4,72,69,1613,18,71,3,datsun 1200 57 | 27,4,97,60,1834,19,71,2,volkswagen model 111 58 | 26,4,91,70,1955,20.5,71,1,plymouth cricket 59 | 24,4,113,95,2278,15.5,72,3,toyota corona hardtop 60 | 25,4,97.5,80,2126,17,72,1,dodge colt hardtop 61 | 23,4,97,54,2254,23.5,72,2,volkswagen type 3 62 | 20,4,140,90,2408,19.5,72,1,chevrolet vega 63 | 21,4,122,86,2226,16.5,72,1,ford pinto runabout 64 | 13,8,350,165,4274,12,72,1,chevrolet impala 65 | 14,8,400,175,4385,12,72,1,pontiac catalina 66 | 15,8,318,150,4135,13.5,72,1,plymouth fury iii 67 | 14,8,351,153,4129,13,72,1,ford galaxie 500 68 | 17,8,304,150,3672,11.5,72,1,amc ambassador sst 69 | 11,8,429,208,4633,11,72,1,mercury marquis 70 | 13,8,350,155,4502,13.5,72,1,buick lesabre custom 71 | 12,8,350,160,4456,13.5,72,1,oldsmobile delta 88 royale 72 | 13,8,400,190,4422,12.5,72,1,chrysler newport royal 73 | 19,3,70,97,2330,13.5,72,3,mazda rx2 coupe 74 | 15,8,304,150,3892,12.5,72,1,amc matador (sw) 75 | 13,8,307,130,4098,14,72,1,chevrolet chevelle concours (sw) 76 | 13,8,302,140,4294,16,72,1,ford gran torino (sw) 77 | 14,8,318,150,4077,14,72,1,plymouth satellite custom (sw) 78 | 18,4,121,112,2933,14.5,72,2,volvo 145e (sw) 79 | 22,4,121,76,2511,18,72,2,volkswagen 411 (sw) 80 | 21,4,120,87,2979,19.5,72,2,peugeot 504 (sw) 81 | 26,4,96,69,2189,18,72,2,renault 12 (sw) 82 | 22,4,122,86,2395,16,72,1,ford pinto (sw) 83 | 28,4,97,92,2288,17,72,3,datsun 510 (sw) 84 | 23,4,120,97,2506,14.5,72,3,toyouta corona mark ii (sw) 85 | 28,4,98,80,2164,15,72,1,dodge colt (sw) 86 | 27,4,97,88,2100,16.5,72,3,toyota corolla 1600 (sw) 87 | 13,8,350,175,4100,13,73,1,buick century 350 88 | 14,8,304,150,3672,11.5,73,1,amc matador 89 | 13,8,350,145,3988,13,73,1,chevrolet malibu 90 | 14,8,302,137,4042,14.5,73,1,ford gran torino 91 | 15,8,318,150,3777,12.5,73,1,dodge coronet custom 92 | 12,8,429,198,4952,11.5,73,1,mercury marquis brougham 93 | 13,8,400,150,4464,12,73,1,chevrolet caprice classic 94 | 13,8,351,158,4363,13,73,1,ford ltd 95 | 14,8,318,150,4237,14.5,73,1,plymouth fury gran sedan 96 | 13,8,440,215,4735,11,73,1,chrysler new yorker brougham 97 | 12,8,455,225,4951,11,73,1,buick electra 225 custom 98 | 13,8,360,175,3821,11,73,1,amc ambassador brougham 99 | 18,6,225,105,3121,16.5,73,1,plymouth valiant 100 | 16,6,250,100,3278,18,73,1,chevrolet nova custom 101 | 18,6,232,100,2945,16,73,1,amc hornet 102 | 18,6,250,88,3021,16.5,73,1,ford maverick 103 | 23,6,198,95,2904,16,73,1,plymouth duster 104 | 26,4,97,46,1950,21,73,2,volkswagen super beetle 105 | 11,8,400,150,4997,14,73,1,chevrolet impala 106 | 12,8,400,167,4906,12.5,73,1,ford country 107 | 13,8,360,170,4654,13,73,1,plymouth custom suburb 108 | 12,8,350,180,4499,12.5,73,1,oldsmobile vista cruiser 109 | 18,6,232,100,2789,15,73,1,amc gremlin 110 | 20,4,97,88,2279,19,73,3,toyota carina 111 | 21,4,140,72,2401,19.5,73,1,chevrolet vega 112 | 22,4,108,94,2379,16.5,73,3,datsun 610 113 | 18,3,70,90,2124,13.5,73,3,maxda rx3 114 | 19,4,122,85,2310,18.5,73,1,ford pinto 115 | 21,6,155,107,2472,14,73,1,mercury capri v6 116 | 26,4,98,90,2265,15.5,73,2,fiat 124 sport coupe 117 | 15,8,350,145,4082,13,73,1,chevrolet monte carlo s 118 | 16,8,400,230,4278,9.5,73,1,pontiac grand prix 119 | 29,4,68,49,1867,19.5,73,2,fiat 128 120 | 24,4,116,75,2158,15.5,73,2,opel manta 121 | 20,4,114,91,2582,14,73,2,audi 100ls 122 | 19,4,121,112,2868,15.5,73,2,volvo 144ea 123 | 15,8,318,150,3399,11,73,1,dodge dart custom 124 | 24,4,121,110,2660,14,73,2,saab 99le 125 | 20,6,156,122,2807,13.5,73,3,toyota mark ii 126 | 11,8,350,180,3664,11,73,1,oldsmobile omega 127 | 20,6,198,95,3102,16.5,74,1,plymouth duster 128 | 21,6,200,?,2875,17,74,1,ford maverick 129 | 19,6,232,100,2901,16,74,1,amc hornet 130 | 15,6,250,100,3336,17,74,1,chevrolet nova 131 | 31,4,79,67,1950,19,74,3,datsun b210 132 | 26,4,122,80,2451,16.5,74,1,ford pinto 133 | 32,4,71,65,1836,21,74,3,toyota corolla 1200 134 | 25,4,140,75,2542,17,74,1,chevrolet vega 135 | 16,6,250,100,3781,17,74,1,chevrolet chevelle malibu classic 136 | 16,6,258,110,3632,18,74,1,amc matador 137 | 18,6,225,105,3613,16.5,74,1,plymouth satellite sebring 138 | 16,8,302,140,4141,14,74,1,ford gran torino 139 | 13,8,350,150,4699,14.5,74,1,buick century luxus (sw) 140 | 14,8,318,150,4457,13.5,74,1,dodge coronet custom (sw) 141 | 14,8,302,140,4638,16,74,1,ford gran torino (sw) 142 | 14,8,304,150,4257,15.5,74,1,amc matador (sw) 143 | 29,4,98,83,2219,16.5,74,2,audi fox 144 | 26,4,79,67,1963,15.5,74,2,volkswagen dasher 145 | 26,4,97,78,2300,14.5,74,2,opel manta 146 | 31,4,76,52,1649,16.5,74,3,toyota corona 147 | 32,4,83,61,2003,19,74,3,datsun 710 148 | 28,4,90,75,2125,14.5,74,1,dodge colt 149 | 24,4,90,75,2108,15.5,74,2,fiat 128 150 | 26,4,116,75,2246,14,74,2,fiat 124 tc 151 | 24,4,120,97,2489,15,74,3,honda civic 152 | 26,4,108,93,2391,15.5,74,3,subaru 153 | 31,4,79,67,2000,16,74,2,fiat x1.9 154 | 19,6,225,95,3264,16,75,1,plymouth valiant custom 155 | 18,6,250,105,3459,16,75,1,chevrolet nova 156 | 15,6,250,72,3432,21,75,1,mercury monarch 157 | 15,6,250,72,3158,19.5,75,1,ford maverick 158 | 16,8,400,170,4668,11.5,75,1,pontiac catalina 159 | 15,8,350,145,4440,14,75,1,chevrolet bel air 160 | 16,8,318,150,4498,14.5,75,1,plymouth grand fury 161 | 14,8,351,148,4657,13.5,75,1,ford ltd 162 | 17,6,231,110,3907,21,75,1,buick century 163 | 16,6,250,105,3897,18.5,75,1,chevroelt chevelle malibu 164 | 15,6,258,110,3730,19,75,1,amc matador 165 | 18,6,225,95,3785,19,75,1,plymouth fury 166 | 21,6,231,110,3039,15,75,1,buick skyhawk 167 | 20,8,262,110,3221,13.5,75,1,chevrolet monza 2+2 168 | 13,8,302,129,3169,12,75,1,ford mustang ii 169 | 29,4,97,75,2171,16,75,3,toyota corolla 170 | 23,4,140,83,2639,17,75,1,ford pinto 171 | 20,6,232,100,2914,16,75,1,amc gremlin 172 | 23,4,140,78,2592,18.5,75,1,pontiac astro 173 | 24,4,134,96,2702,13.5,75,3,toyota corona 174 | 25,4,90,71,2223,16.5,75,2,volkswagen dasher 175 | 24,4,119,97,2545,17,75,3,datsun 710 176 | 18,6,171,97,2984,14.5,75,1,ford pinto 177 | 29,4,90,70,1937,14,75,2,volkswagen rabbit 178 | 19,6,232,90,3211,17,75,1,amc pacer 179 | 23,4,115,95,2694,15,75,2,audi 100ls 180 | 23,4,120,88,2957,17,75,2,peugeot 504 181 | 22,4,121,98,2945,14.5,75,2,volvo 244dl 182 | 25,4,121,115,2671,13.5,75,2,saab 99le 183 | 33,4,91,53,1795,17.5,75,3,honda civic cvcc 184 | 28,4,107,86,2464,15.5,76,2,fiat 131 185 | 25,4,116,81,2220,16.9,76,2,opel 1900 186 | 25,4,140,92,2572,14.9,76,1,capri ii 187 | 26,4,98,79,2255,17.7,76,1,dodge colt 188 | 27,4,101,83,2202,15.3,76,2,renault 12tl 189 | 17.5,8,305,140,4215,13,76,1,chevrolet chevelle malibu classic 190 | 16,8,318,150,4190,13,76,1,dodge coronet brougham 191 | 15.5,8,304,120,3962,13.9,76,1,amc matador 192 | 14.5,8,351,152,4215,12.8,76,1,ford gran torino 193 | 22,6,225,100,3233,15.4,76,1,plymouth valiant 194 | 22,6,250,105,3353,14.5,76,1,chevrolet nova 195 | 24,6,200,81,3012,17.6,76,1,ford maverick 196 | 22.5,6,232,90,3085,17.6,76,1,amc hornet 197 | 29,4,85,52,2035,22.2,76,1,chevrolet chevette 198 | 24.5,4,98,60,2164,22.1,76,1,chevrolet woody 199 | 29,4,90,70,1937,14.2,76,2,vw rabbit 200 | 33,4,91,53,1795,17.4,76,3,honda civic 201 | 20,6,225,100,3651,17.7,76,1,dodge aspen se 202 | 18,6,250,78,3574,21,76,1,ford granada ghia 203 | 18.5,6,250,110,3645,16.2,76,1,pontiac ventura sj 204 | 17.5,6,258,95,3193,17.8,76,1,amc pacer d/l 205 | 29.5,4,97,71,1825,12.2,76,2,volkswagen rabbit 206 | 32,4,85,70,1990,17,76,3,datsun b-210 207 | 28,4,97,75,2155,16.4,76,3,toyota corolla 208 | 26.5,4,140,72,2565,13.6,76,1,ford pinto 209 | 20,4,130,102,3150,15.7,76,2,volvo 245 210 | 13,8,318,150,3940,13.2,76,1,plymouth volare premier v8 211 | 19,4,120,88,3270,21.9,76,2,peugeot 504 212 | 19,6,156,108,2930,15.5,76,3,toyota mark ii 213 | 16.5,6,168,120,3820,16.7,76,2,mercedes-benz 280s 214 | 16.5,8,350,180,4380,12.1,76,1,cadillac seville 215 | 13,8,350,145,4055,12,76,1,chevy c10 216 | 13,8,302,130,3870,15,76,1,ford f108 217 | 13,8,318,150,3755,14,76,1,dodge d100 218 | 31.5,4,98,68,2045,18.5,77,3,honda accord cvcc 219 | 30,4,111,80,2155,14.8,77,1,buick opel isuzu deluxe 220 | 36,4,79,58,1825,18.6,77,2,renault 5 gtl 221 | 25.5,4,122,96,2300,15.5,77,1,plymouth arrow gs 222 | 33.5,4,85,70,1945,16.8,77,3,datsun f-10 hatchback 223 | 17.5,8,305,145,3880,12.5,77,1,chevrolet caprice classic 224 | 17,8,260,110,4060,19,77,1,oldsmobile cutlass supreme 225 | 15.5,8,318,145,4140,13.7,77,1,dodge monaco brougham 226 | 15,8,302,130,4295,14.9,77,1,mercury cougar brougham 227 | 17.5,6,250,110,3520,16.4,77,1,chevrolet concours 228 | 20.5,6,231,105,3425,16.9,77,1,buick skylark 229 | 19,6,225,100,3630,17.7,77,1,plymouth volare custom 230 | 18.5,6,250,98,3525,19,77,1,ford granada 231 | 16,8,400,180,4220,11.1,77,1,pontiac grand prix lj 232 | 15.5,8,350,170,4165,11.4,77,1,chevrolet monte carlo landau 233 | 15.5,8,400,190,4325,12.2,77,1,chrysler cordoba 234 | 16,8,351,149,4335,14.5,77,1,ford thunderbird 235 | 29,4,97,78,1940,14.5,77,2,volkswagen rabbit custom 236 | 24.5,4,151,88,2740,16,77,1,pontiac sunbird coupe 237 | 26,4,97,75,2265,18.2,77,3,toyota corolla liftback 238 | 25.5,4,140,89,2755,15.8,77,1,ford mustang ii 2+2 239 | 30.5,4,98,63,2051,17,77,1,chevrolet chevette 240 | 33.5,4,98,83,2075,15.9,77,1,dodge colt m/m 241 | 30,4,97,67,1985,16.4,77,3,subaru dl 242 | 30.5,4,97,78,2190,14.1,77,2,volkswagen dasher 243 | 22,6,146,97,2815,14.5,77,3,datsun 810 244 | 21.5,4,121,110,2600,12.8,77,2,bmw 320i 245 | 21.5,3,80,110,2720,13.5,77,3,mazda rx-4 246 | 43.1,4,90,48,1985,21.5,78,2,volkswagen rabbit custom diesel 247 | 36.1,4,98,66,1800,14.4,78,1,ford fiesta 248 | 32.8,4,78,52,1985,19.4,78,3,mazda glc deluxe 249 | 39.4,4,85,70,2070,18.6,78,3,datsun b210 gx 250 | 36.1,4,91,60,1800,16.4,78,3,honda civic cvcc 251 | 19.9,8,260,110,3365,15.5,78,1,oldsmobile cutlass salon brougham 252 | 19.4,8,318,140,3735,13.2,78,1,dodge diplomat 253 | 20.2,8,302,139,3570,12.8,78,1,mercury monarch ghia 254 | 19.2,6,231,105,3535,19.2,78,1,pontiac phoenix lj 255 | 20.5,6,200,95,3155,18.2,78,1,chevrolet malibu 256 | 20.2,6,200,85,2965,15.8,78,1,ford fairmont (auto) 257 | 25.1,4,140,88,2720,15.4,78,1,ford fairmont (man) 258 | 20.5,6,225,100,3430,17.2,78,1,plymouth volare 259 | 19.4,6,232,90,3210,17.2,78,1,amc concord 260 | 20.6,6,231,105,3380,15.8,78,1,buick century special 261 | 20.8,6,200,85,3070,16.7,78,1,mercury zephyr 262 | 18.6,6,225,110,3620,18.7,78,1,dodge aspen 263 | 18.1,6,258,120,3410,15.1,78,1,amc concord d/l 264 | 19.2,8,305,145,3425,13.2,78,1,chevrolet monte carlo landau 265 | 17.7,6,231,165,3445,13.4,78,1,buick regal sport coupe (turbo) 266 | 18.1,8,302,139,3205,11.2,78,1,ford futura 267 | 17.5,8,318,140,4080,13.7,78,1,dodge magnum xe 268 | 30,4,98,68,2155,16.5,78,1,chevrolet chevette 269 | 27.5,4,134,95,2560,14.2,78,3,toyota corona 270 | 27.2,4,119,97,2300,14.7,78,3,datsun 510 271 | 30.9,4,105,75,2230,14.5,78,1,dodge omni 272 | 21.1,4,134,95,2515,14.8,78,3,toyota celica gt liftback 273 | 23.2,4,156,105,2745,16.7,78,1,plymouth sapporo 274 | 23.8,4,151,85,2855,17.6,78,1,oldsmobile starfire sx 275 | 23.9,4,119,97,2405,14.9,78,3,datsun 200-sx 276 | 20.3,5,131,103,2830,15.9,78,2,audi 5000 277 | 17,6,163,125,3140,13.6,78,2,volvo 264gl 278 | 21.6,4,121,115,2795,15.7,78,2,saab 99gle 279 | 16.2,6,163,133,3410,15.8,78,2,peugeot 604sl 280 | 31.5,4,89,71,1990,14.9,78,2,volkswagen scirocco 281 | 29.5,4,98,68,2135,16.6,78,3,honda accord lx 282 | 21.5,6,231,115,3245,15.4,79,1,pontiac lemans v6 283 | 19.8,6,200,85,2990,18.2,79,1,mercury zephyr 6 284 | 22.3,4,140,88,2890,17.3,79,1,ford fairmont 4 285 | 20.2,6,232,90,3265,18.2,79,1,amc concord dl 6 286 | 20.6,6,225,110,3360,16.6,79,1,dodge aspen 6 287 | 17,8,305,130,3840,15.4,79,1,chevrolet caprice classic 288 | 17.6,8,302,129,3725,13.4,79,1,ford ltd landau 289 | 16.5,8,351,138,3955,13.2,79,1,mercury grand marquis 290 | 18.2,8,318,135,3830,15.2,79,1,dodge st. regis 291 | 16.9,8,350,155,4360,14.9,79,1,buick estate wagon (sw) 292 | 15.5,8,351,142,4054,14.3,79,1,ford country squire (sw) 293 | 19.2,8,267,125,3605,15,79,1,chevrolet malibu classic (sw) 294 | 18.5,8,360,150,3940,13,79,1,chrysler lebaron town @ country (sw) 295 | 31.9,4,89,71,1925,14,79,2,vw rabbit custom 296 | 34.1,4,86,65,1975,15.2,79,3,maxda glc deluxe 297 | 35.7,4,98,80,1915,14.4,79,1,dodge colt hatchback custom 298 | 27.4,4,121,80,2670,15,79,1,amc spirit dl 299 | 25.4,5,183,77,3530,20.1,79,2,mercedes benz 300d 300 | 23,8,350,125,3900,17.4,79,1,cadillac eldorado 301 | 27.2,4,141,71,3190,24.8,79,2,peugeot 504 302 | 23.9,8,260,90,3420,22.2,79,1,oldsmobile cutlass salon brougham 303 | 34.2,4,105,70,2200,13.2,79,1,plymouth horizon 304 | 34.5,4,105,70,2150,14.9,79,1,plymouth horizon tc3 305 | 31.8,4,85,65,2020,19.2,79,3,datsun 210 306 | 37.3,4,91,69,2130,14.7,79,2,fiat strada custom 307 | 28.4,4,151,90,2670,16,79,1,buick skylark limited 308 | 28.8,6,173,115,2595,11.3,79,1,chevrolet citation 309 | 26.8,6,173,115,2700,12.9,79,1,oldsmobile omega brougham 310 | 33.5,4,151,90,2556,13.2,79,1,pontiac phoenix 311 | 41.5,4,98,76,2144,14.7,80,2,vw rabbit 312 | 38.1,4,89,60,1968,18.8,80,3,toyota corolla tercel 313 | 32.1,4,98,70,2120,15.5,80,1,chevrolet chevette 314 | 37.2,4,86,65,2019,16.4,80,3,datsun 310 315 | 28,4,151,90,2678,16.5,80,1,chevrolet citation 316 | 26.4,4,140,88,2870,18.1,80,1,ford fairmont 317 | 24.3,4,151,90,3003,20.1,80,1,amc concord 318 | 19.1,6,225,90,3381,18.7,80,1,dodge aspen 319 | 34.3,4,97,78,2188,15.8,80,2,audi 4000 320 | 29.8,4,134,90,2711,15.5,80,3,toyota corona liftback 321 | 31.3,4,120,75,2542,17.5,80,3,mazda 626 322 | 37,4,119,92,2434,15,80,3,datsun 510 hatchback 323 | 32.2,4,108,75,2265,15.2,80,3,toyota corolla 324 | 46.6,4,86,65,2110,17.9,80,3,mazda glc 325 | 27.9,4,156,105,2800,14.4,80,1,dodge colt 326 | 40.8,4,85,65,2110,19.2,80,3,datsun 210 327 | 44.3,4,90,48,2085,21.7,80,2,vw rabbit c (diesel) 328 | 43.4,4,90,48,2335,23.7,80,2,vw dasher (diesel) 329 | 36.4,5,121,67,2950,19.9,80,2,audi 5000s (diesel) 330 | 30,4,146,67,3250,21.8,80,2,mercedes-benz 240d 331 | 44.6,4,91,67,1850,13.8,80,3,honda civic 1500 gl 332 | 40.9,4,85,?,1835,17.3,80,2,renault lecar deluxe 333 | 33.8,4,97,67,2145,18,80,3,subaru dl 334 | 29.8,4,89,62,1845,15.3,80,2,vokswagen rabbit 335 | 32.7,6,168,132,2910,11.4,80,3,datsun 280-zx 336 | 23.7,3,70,100,2420,12.5,80,3,mazda rx-7 gs 337 | 35,4,122,88,2500,15.1,80,2,triumph tr7 coupe 338 | 23.6,4,140,?,2905,14.3,80,1,ford mustang cobra 339 | 32.4,4,107,72,2290,17,80,3,honda accord 340 | 27.2,4,135,84,2490,15.7,81,1,plymouth reliant 341 | 26.6,4,151,84,2635,16.4,81,1,buick skylark 342 | 25.8,4,156,92,2620,14.4,81,1,dodge aries wagon (sw) 343 | 23.5,6,173,110,2725,12.6,81,1,chevrolet citation 344 | 30,4,135,84,2385,12.9,81,1,plymouth reliant 345 | 39.1,4,79,58,1755,16.9,81,3,toyota starlet 346 | 39,4,86,64,1875,16.4,81,1,plymouth champ 347 | 35.1,4,81,60,1760,16.1,81,3,honda civic 1300 348 | 32.3,4,97,67,2065,17.8,81,3,subaru 349 | 37,4,85,65,1975,19.4,81,3,datsun 210 mpg 350 | 37.7,4,89,62,2050,17.3,81,3,toyota tercel 351 | 34.1,4,91,68,1985,16,81,3,mazda glc 4 352 | 34.7,4,105,63,2215,14.9,81,1,plymouth horizon 4 353 | 34.4,4,98,65,2045,16.2,81,1,ford escort 4w 354 | 29.9,4,98,65,2380,20.7,81,1,ford escort 2h 355 | 33,4,105,74,2190,14.2,81,2,volkswagen jetta 356 | 34.5,4,100,?,2320,15.8,81,2,renault 18i 357 | 33.7,4,107,75,2210,14.4,81,3,honda prelude 358 | 32.4,4,108,75,2350,16.8,81,3,toyota corolla 359 | 32.9,4,119,100,2615,14.8,81,3,datsun 200sx 360 | 31.6,4,120,74,2635,18.3,81,3,mazda 626 361 | 28.1,4,141,80,3230,20.4,81,2,peugeot 505s turbo diesel 362 | 30.7,6,145,76,3160,19.6,81,2,volvo diesel 363 | 25.4,6,168,116,2900,12.6,81,3,toyota cressida 364 | 24.2,6,146,120,2930,13.8,81,3,datsun 810 maxima 365 | 22.4,6,231,110,3415,15.8,81,1,buick century 366 | 26.6,8,350,105,3725,19,81,1,oldsmobile cutlass ls 367 | 20.2,6,200,88,3060,17.1,81,1,ford granada gl 368 | 17.6,6,225,85,3465,16.6,81,1,chrysler lebaron salon 369 | 28,4,112,88,2605,19.6,82,1,chevrolet cavalier 370 | 27,4,112,88,2640,18.6,82,1,chevrolet cavalier wagon 371 | 34,4,112,88,2395,18,82,1,chevrolet cavalier 2-door 372 | 31,4,112,85,2575,16.2,82,1,pontiac j2000 se hatchback 373 | 29,4,135,84,2525,16,82,1,dodge aries se 374 | 27,4,151,90,2735,18,82,1,pontiac phoenix 375 | 24,4,140,92,2865,16.4,82,1,ford fairmont futura 376 | 36,4,105,74,1980,15.3,82,2,volkswagen rabbit l 377 | 37,4,91,68,2025,18.2,82,3,mazda glc custom l 378 | 31,4,91,68,1970,17.6,82,3,mazda glc custom 379 | 38,4,105,63,2125,14.7,82,1,plymouth horizon miser 380 | 36,4,98,70,2125,17.3,82,1,mercury lynx l 381 | 36,4,120,88,2160,14.5,82,3,nissan stanza xe 382 | 36,4,107,75,2205,14.5,82,3,honda accord 383 | 34,4,108,70,2245,16.9,82,3,toyota corolla 384 | 38,4,91,67,1965,15,82,3,honda civic 385 | 32,4,91,67,1965,15.7,82,3,honda civic (auto) 386 | 38,4,91,67,1995,16.2,82,3,datsun 310 gx 387 | 25,6,181,110,2945,16.4,82,1,buick century limited 388 | 38,6,262,85,3015,17,82,1,oldsmobile cutlass ciera (diesel) 389 | 26,4,156,92,2585,14.5,82,1,chrysler lebaron medallion 390 | 22,6,232,112,2835,14.7,82,1,ford granada l 391 | 32,4,144,96,2665,13.9,82,3,toyota celica gt 392 | 36,4,135,84,2370,13,82,1,dodge charger 2.2 393 | 27,4,151,90,2950,17.3,82,1,chevrolet camaro 394 | 27,4,140,86,2790,15.6,82,1,ford mustang gl 395 | 44,4,97,52,2130,24.6,82,2,vw pickup 396 | 32,4,135,84,2295,11.6,82,1,dodge rampage 397 | 28,4,120,79,2625,18.6,82,1,ford ranger 398 | 31,4,119,82,2720,19.4,82,1,chevy s-10 399 | -------------------------------------------------------------------------------- /Data/Auto.data: -------------------------------------------------------------------------------- 1 | mpg cylinders displacement horsepower weight acceleration year origin name 2 | 18.0 8 307.0 130.0 3504. 12.0 70 1 "chevrolet chevelle malibu" 3 | 15.0 8 350.0 165.0 3693. 11.5 70 1 "buick skylark 320" 4 | 18.0 8 318.0 150.0 3436. 11.0 70 1 "plymouth satellite" 5 | 16.0 8 304.0 150.0 3433. 12.0 70 1 "amc rebel sst" 6 | 17.0 8 302.0 140.0 3449. 10.5 70 1 "ford torino" 7 | 15.0 8 429.0 198.0 4341. 10.0 70 1 "ford galaxie 500" 8 | 14.0 8 454.0 220.0 4354. 9.0 70 1 "chevrolet impala" 9 | 14.0 8 440.0 215.0 4312. 8.5 70 1 "plymouth fury iii" 10 | 14.0 8 455.0 225.0 4425. 10.0 70 1 "pontiac catalina" 11 | 15.0 8 390.0 190.0 3850. 8.5 70 1 "amc ambassador dpl" 12 | 15.0 8 383.0 170.0 3563. 10.0 70 1 "dodge challenger se" 13 | 14.0 8 340.0 160.0 3609. 8.0 70 1 "plymouth 'cuda 340" 14 | 15.0 8 400.0 150.0 3761. 9.5 70 1 "chevrolet monte carlo" 15 | 14.0 8 455.0 225.0 3086. 10.0 70 1 "buick estate wagon (sw)" 16 | 24.0 4 113.0 95.00 2372. 15.0 70 3 "toyota corona mark ii" 17 | 22.0 6 198.0 95.00 2833. 15.5 70 1 "plymouth duster" 18 | 18.0 6 199.0 97.00 2774. 15.5 70 1 "amc hornet" 19 | 21.0 6 200.0 85.00 2587. 16.0 70 1 "ford maverick" 20 | 27.0 4 97.00 88.00 2130. 14.5 70 3 "datsun pl510" 21 | 26.0 4 97.00 46.00 1835. 20.5 70 2 "volkswagen 1131 deluxe sedan" 22 | 25.0 4 110.0 87.00 2672. 17.5 70 2 "peugeot 504" 23 | 24.0 4 107.0 90.00 2430. 14.5 70 2 "audi 100 ls" 24 | 25.0 4 104.0 95.00 2375. 17.5 70 2 "saab 99e" 25 | 26.0 4 121.0 113.0 2234. 12.5 70 2 "bmw 2002" 26 | 21.0 6 199.0 90.00 2648. 15.0 70 1 "amc gremlin" 27 | 10.0 8 360.0 215.0 4615. 14.0 70 1 "ford f250" 28 | 10.0 8 307.0 200.0 4376. 15.0 70 1 "chevy c20" 29 | 11.0 8 318.0 210.0 4382. 13.5 70 1 "dodge d200" 30 | 9.0 8 304.0 193.0 4732. 18.5 70 1 "hi 1200d" 31 | 27.0 4 97.00 88.00 2130. 14.5 71 3 "datsun pl510" 32 | 28.0 4 140.0 90.00 2264. 15.5 71 1 "chevrolet vega 2300" 33 | 25.0 4 113.0 95.00 2228. 14.0 71 3 "toyota corona" 34 | 25.0 4 98.00 ? 2046. 19.0 71 1 "ford pinto" 35 | 19.0 6 232.0 100.0 2634. 13.0 71 1 "amc gremlin" 36 | 16.0 6 225.0 105.0 3439. 15.5 71 1 "plymouth satellite custom" 37 | 17.0 6 250.0 100.0 3329. 15.5 71 1 "chevrolet chevelle malibu" 38 | 19.0 6 250.0 88.00 3302. 15.5 71 1 "ford torino 500" 39 | 18.0 6 232.0 100.0 3288. 15.5 71 1 "amc matador" 40 | 14.0 8 350.0 165.0 4209. 12.0 71 1 "chevrolet impala" 41 | 14.0 8 400.0 175.0 4464. 11.5 71 1 "pontiac catalina brougham" 42 | 14.0 8 351.0 153.0 4154. 13.5 71 1 "ford galaxie 500" 43 | 14.0 8 318.0 150.0 4096. 13.0 71 1 "plymouth fury iii" 44 | 12.0 8 383.0 180.0 4955. 11.5 71 1 "dodge monaco (sw)" 45 | 13.0 8 400.0 170.0 4746. 12.0 71 1 "ford country squire (sw)" 46 | 13.0 8 400.0 175.0 5140. 12.0 71 1 "pontiac safari (sw)" 47 | 18.0 6 258.0 110.0 2962. 13.5 71 1 "amc hornet sportabout (sw)" 48 | 22.0 4 140.0 72.00 2408. 19.0 71 1 "chevrolet vega (sw)" 49 | 19.0 6 250.0 100.0 3282. 15.0 71 1 "pontiac firebird" 50 | 18.0 6 250.0 88.00 3139. 14.5 71 1 "ford mustang" 51 | 23.0 4 122.0 86.00 2220. 14.0 71 1 "mercury capri 2000" 52 | 28.0 4 116.0 90.00 2123. 14.0 71 2 "opel 1900" 53 | 30.0 4 79.00 70.00 2074. 19.5 71 2 "peugeot 304" 54 | 30.0 4 88.00 76.00 2065. 14.5 71 2 "fiat 124b" 55 | 31.0 4 71.00 65.00 1773. 19.0 71 3 "toyota corolla 1200" 56 | 35.0 4 72.00 69.00 1613. 18.0 71 3 "datsun 1200" 57 | 27.0 4 97.00 60.00 1834. 19.0 71 2 "volkswagen model 111" 58 | 26.0 4 91.00 70.00 1955. 20.5 71 1 "plymouth cricket" 59 | 24.0 4 113.0 95.00 2278. 15.5 72 3 "toyota corona hardtop" 60 | 25.0 4 97.50 80.00 2126. 17.0 72 1 "dodge colt hardtop" 61 | 23.0 4 97.00 54.00 2254. 23.5 72 2 "volkswagen type 3" 62 | 20.0 4 140.0 90.00 2408. 19.5 72 1 "chevrolet vega" 63 | 21.0 4 122.0 86.00 2226. 16.5 72 1 "ford pinto runabout" 64 | 13.0 8 350.0 165.0 4274. 12.0 72 1 "chevrolet impala" 65 | 14.0 8 400.0 175.0 4385. 12.0 72 1 "pontiac catalina" 66 | 15.0 8 318.0 150.0 4135. 13.5 72 1 "plymouth fury iii" 67 | 14.0 8 351.0 153.0 4129. 13.0 72 1 "ford galaxie 500" 68 | 17.0 8 304.0 150.0 3672. 11.5 72 1 "amc ambassador sst" 69 | 11.0 8 429.0 208.0 4633. 11.0 72 1 "mercury marquis" 70 | 13.0 8 350.0 155.0 4502. 13.5 72 1 "buick lesabre custom" 71 | 12.0 8 350.0 160.0 4456. 13.5 72 1 "oldsmobile delta 88 royale" 72 | 13.0 8 400.0 190.0 4422. 12.5 72 1 "chrysler newport royal" 73 | 19.0 3 70.00 97.00 2330. 13.5 72 3 "mazda rx2 coupe" 74 | 15.0 8 304.0 150.0 3892. 12.5 72 1 "amc matador (sw)" 75 | 13.0 8 307.0 130.0 4098. 14.0 72 1 "chevrolet chevelle concours (sw)" 76 | 13.0 8 302.0 140.0 4294. 16.0 72 1 "ford gran torino (sw)" 77 | 14.0 8 318.0 150.0 4077. 14.0 72 1 "plymouth satellite custom (sw)" 78 | 18.0 4 121.0 112.0 2933. 14.5 72 2 "volvo 145e (sw)" 79 | 22.0 4 121.0 76.00 2511. 18.0 72 2 "volkswagen 411 (sw)" 80 | 21.0 4 120.0 87.00 2979. 19.5 72 2 "peugeot 504 (sw)" 81 | 26.0 4 96.00 69.00 2189. 18.0 72 2 "renault 12 (sw)" 82 | 22.0 4 122.0 86.00 2395. 16.0 72 1 "ford pinto (sw)" 83 | 28.0 4 97.00 92.00 2288. 17.0 72 3 "datsun 510 (sw)" 84 | 23.0 4 120.0 97.00 2506. 14.5 72 3 "toyouta corona mark ii (sw)" 85 | 28.0 4 98.00 80.00 2164. 15.0 72 1 "dodge colt (sw)" 86 | 27.0 4 97.00 88.00 2100. 16.5 72 3 "toyota corolla 1600 (sw)" 87 | 13.0 8 350.0 175.0 4100. 13.0 73 1 "buick century 350" 88 | 14.0 8 304.0 150.0 3672. 11.5 73 1 "amc matador" 89 | 13.0 8 350.0 145.0 3988. 13.0 73 1 "chevrolet malibu" 90 | 14.0 8 302.0 137.0 4042. 14.5 73 1 "ford gran torino" 91 | 15.0 8 318.0 150.0 3777. 12.5 73 1 "dodge coronet custom" 92 | 12.0 8 429.0 198.0 4952. 11.5 73 1 "mercury marquis brougham" 93 | 13.0 8 400.0 150.0 4464. 12.0 73 1 "chevrolet caprice classic" 94 | 13.0 8 351.0 158.0 4363. 13.0 73 1 "ford ltd" 95 | 14.0 8 318.0 150.0 4237. 14.5 73 1 "plymouth fury gran sedan" 96 | 13.0 8 440.0 215.0 4735. 11.0 73 1 "chrysler new yorker brougham" 97 | 12.0 8 455.0 225.0 4951. 11.0 73 1 "buick electra 225 custom" 98 | 13.0 8 360.0 175.0 3821. 11.0 73 1 "amc ambassador brougham" 99 | 18.0 6 225.0 105.0 3121. 16.5 73 1 "plymouth valiant" 100 | 16.0 6 250.0 100.0 3278. 18.0 73 1 "chevrolet nova custom" 101 | 18.0 6 232.0 100.0 2945. 16.0 73 1 "amc hornet" 102 | 18.0 6 250.0 88.00 3021. 16.5 73 1 "ford maverick" 103 | 23.0 6 198.0 95.00 2904. 16.0 73 1 "plymouth duster" 104 | 26.0 4 97.00 46.00 1950. 21.0 73 2 "volkswagen super beetle" 105 | 11.0 8 400.0 150.0 4997. 14.0 73 1 "chevrolet impala" 106 | 12.0 8 400.0 167.0 4906. 12.5 73 1 "ford country" 107 | 13.0 8 360.0 170.0 4654. 13.0 73 1 "plymouth custom suburb" 108 | 12.0 8 350.0 180.0 4499. 12.5 73 1 "oldsmobile vista cruiser" 109 | 18.0 6 232.0 100.0 2789. 15.0 73 1 "amc gremlin" 110 | 20.0 4 97.00 88.00 2279. 19.0 73 3 "toyota carina" 111 | 21.0 4 140.0 72.00 2401. 19.5 73 1 "chevrolet vega" 112 | 22.0 4 108.0 94.00 2379. 16.5 73 3 "datsun 610" 113 | 18.0 3 70.00 90.00 2124. 13.5 73 3 "maxda rx3" 114 | 19.0 4 122.0 85.00 2310. 18.5 73 1 "ford pinto" 115 | 21.0 6 155.0 107.0 2472. 14.0 73 1 "mercury capri v6" 116 | 26.0 4 98.00 90.00 2265. 15.5 73 2 "fiat 124 sport coupe" 117 | 15.0 8 350.0 145.0 4082. 13.0 73 1 "chevrolet monte carlo s" 118 | 16.0 8 400.0 230.0 4278. 9.50 73 1 "pontiac grand prix" 119 | 29.0 4 68.00 49.00 1867. 19.5 73 2 "fiat 128" 120 | 24.0 4 116.0 75.00 2158. 15.5 73 2 "opel manta" 121 | 20.0 4 114.0 91.00 2582. 14.0 73 2 "audi 100ls" 122 | 19.0 4 121.0 112.0 2868. 15.5 73 2 "volvo 144ea" 123 | 15.0 8 318.0 150.0 3399. 11.0 73 1 "dodge dart custom" 124 | 24.0 4 121.0 110.0 2660. 14.0 73 2 "saab 99le" 125 | 20.0 6 156.0 122.0 2807. 13.5 73 3 "toyota mark ii" 126 | 11.0 8 350.0 180.0 3664. 11.0 73 1 "oldsmobile omega" 127 | 20.0 6 198.0 95.00 3102. 16.5 74 1 "plymouth duster" 128 | 21.0 6 200.0 ? 2875. 17.0 74 1 "ford maverick" 129 | 19.0 6 232.0 100.0 2901. 16.0 74 1 "amc hornet" 130 | 15.0 6 250.0 100.0 3336. 17.0 74 1 "chevrolet nova" 131 | 31.0 4 79.00 67.00 1950. 19.0 74 3 "datsun b210" 132 | 26.0 4 122.0 80.00 2451. 16.5 74 1 "ford pinto" 133 | 32.0 4 71.00 65.00 1836. 21.0 74 3 "toyota corolla 1200" 134 | 25.0 4 140.0 75.00 2542. 17.0 74 1 "chevrolet vega" 135 | 16.0 6 250.0 100.0 3781. 17.0 74 1 "chevrolet chevelle malibu classic" 136 | 16.0 6 258.0 110.0 3632. 18.0 74 1 "amc matador" 137 | 18.0 6 225.0 105.0 3613. 16.5 74 1 "plymouth satellite sebring" 138 | 16.0 8 302.0 140.0 4141. 14.0 74 1 "ford gran torino" 139 | 13.0 8 350.0 150.0 4699. 14.5 74 1 "buick century luxus (sw)" 140 | 14.0 8 318.0 150.0 4457. 13.5 74 1 "dodge coronet custom (sw)" 141 | 14.0 8 302.0 140.0 4638. 16.0 74 1 "ford gran torino (sw)" 142 | 14.0 8 304.0 150.0 4257. 15.5 74 1 "amc matador (sw)" 143 | 29.0 4 98.00 83.00 2219. 16.5 74 2 "audi fox" 144 | 26.0 4 79.00 67.00 1963. 15.5 74 2 "volkswagen dasher" 145 | 26.0 4 97.00 78.00 2300. 14.5 74 2 "opel manta" 146 | 31.0 4 76.00 52.00 1649. 16.5 74 3 "toyota corona" 147 | 32.0 4 83.00 61.00 2003. 19.0 74 3 "datsun 710" 148 | 28.0 4 90.00 75.00 2125. 14.5 74 1 "dodge colt" 149 | 24.0 4 90.00 75.00 2108. 15.5 74 2 "fiat 128" 150 | 26.0 4 116.0 75.00 2246. 14.0 74 2 "fiat 124 tc" 151 | 24.0 4 120.0 97.00 2489. 15.0 74 3 "honda civic" 152 | 26.0 4 108.0 93.00 2391. 15.5 74 3 "subaru" 153 | 31.0 4 79.00 67.00 2000. 16.0 74 2 "fiat x1.9" 154 | 19.0 6 225.0 95.00 3264. 16.0 75 1 "plymouth valiant custom" 155 | 18.0 6 250.0 105.0 3459. 16.0 75 1 "chevrolet nova" 156 | 15.0 6 250.0 72.00 3432. 21.0 75 1 "mercury monarch" 157 | 15.0 6 250.0 72.00 3158. 19.5 75 1 "ford maverick" 158 | 16.0 8 400.0 170.0 4668. 11.5 75 1 "pontiac catalina" 159 | 15.0 8 350.0 145.0 4440. 14.0 75 1 "chevrolet bel air" 160 | 16.0 8 318.0 150.0 4498. 14.5 75 1 "plymouth grand fury" 161 | 14.0 8 351.0 148.0 4657. 13.5 75 1 "ford ltd" 162 | 17.0 6 231.0 110.0 3907. 21.0 75 1 "buick century" 163 | 16.0 6 250.0 105.0 3897. 18.5 75 1 "chevroelt chevelle malibu" 164 | 15.0 6 258.0 110.0 3730. 19.0 75 1 "amc matador" 165 | 18.0 6 225.0 95.00 3785. 19.0 75 1 "plymouth fury" 166 | 21.0 6 231.0 110.0 3039. 15.0 75 1 "buick skyhawk" 167 | 20.0 8 262.0 110.0 3221. 13.5 75 1 "chevrolet monza 2+2" 168 | 13.0 8 302.0 129.0 3169. 12.0 75 1 "ford mustang ii" 169 | 29.0 4 97.00 75.00 2171. 16.0 75 3 "toyota corolla" 170 | 23.0 4 140.0 83.00 2639. 17.0 75 1 "ford pinto" 171 | 20.0 6 232.0 100.0 2914. 16.0 75 1 "amc gremlin" 172 | 23.0 4 140.0 78.00 2592. 18.5 75 1 "pontiac astro" 173 | 24.0 4 134.0 96.00 2702. 13.5 75 3 "toyota corona" 174 | 25.0 4 90.00 71.00 2223. 16.5 75 2 "volkswagen dasher" 175 | 24.0 4 119.0 97.00 2545. 17.0 75 3 "datsun 710" 176 | 18.0 6 171.0 97.00 2984. 14.5 75 1 "ford pinto" 177 | 29.0 4 90.00 70.00 1937. 14.0 75 2 "volkswagen rabbit" 178 | 19.0 6 232.0 90.00 3211. 17.0 75 1 "amc pacer" 179 | 23.0 4 115.0 95.00 2694. 15.0 75 2 "audi 100ls" 180 | 23.0 4 120.0 88.00 2957. 17.0 75 2 "peugeot 504" 181 | 22.0 4 121.0 98.00 2945. 14.5 75 2 "volvo 244dl" 182 | 25.0 4 121.0 115.0 2671. 13.5 75 2 "saab 99le" 183 | 33.0 4 91.00 53.00 1795. 17.5 75 3 "honda civic cvcc" 184 | 28.0 4 107.0 86.00 2464. 15.5 76 2 "fiat 131" 185 | 25.0 4 116.0 81.00 2220. 16.9 76 2 "opel 1900" 186 | 25.0 4 140.0 92.00 2572. 14.9 76 1 "capri ii" 187 | 26.0 4 98.00 79.00 2255. 17.7 76 1 "dodge colt" 188 | 27.0 4 101.0 83.00 2202. 15.3 76 2 "renault 12tl" 189 | 17.5 8 305.0 140.0 4215. 13.0 76 1 "chevrolet chevelle malibu classic" 190 | 16.0 8 318.0 150.0 4190. 13.0 76 1 "dodge coronet brougham" 191 | 15.5 8 304.0 120.0 3962. 13.9 76 1 "amc matador" 192 | 14.5 8 351.0 152.0 4215. 12.8 76 1 "ford gran torino" 193 | 22.0 6 225.0 100.0 3233. 15.4 76 1 "plymouth valiant" 194 | 22.0 6 250.0 105.0 3353. 14.5 76 1 "chevrolet nova" 195 | 24.0 6 200.0 81.00 3012. 17.6 76 1 "ford maverick" 196 | 22.5 6 232.0 90.00 3085. 17.6 76 1 "amc hornet" 197 | 29.0 4 85.00 52.00 2035. 22.2 76 1 "chevrolet chevette" 198 | 24.5 4 98.00 60.00 2164. 22.1 76 1 "chevrolet woody" 199 | 29.0 4 90.00 70.00 1937. 14.2 76 2 "vw rabbit" 200 | 33.0 4 91.00 53.00 1795. 17.4 76 3 "honda civic" 201 | 20.0 6 225.0 100.0 3651. 17.7 76 1 "dodge aspen se" 202 | 18.0 6 250.0 78.00 3574. 21.0 76 1 "ford granada ghia" 203 | 18.5 6 250.0 110.0 3645. 16.2 76 1 "pontiac ventura sj" 204 | 17.5 6 258.0 95.00 3193. 17.8 76 1 "amc pacer d/l" 205 | 29.5 4 97.00 71.00 1825. 12.2 76 2 "volkswagen rabbit" 206 | 32.0 4 85.00 70.00 1990. 17.0 76 3 "datsun b-210" 207 | 28.0 4 97.00 75.00 2155. 16.4 76 3 "toyota corolla" 208 | 26.5 4 140.0 72.00 2565. 13.6 76 1 "ford pinto" 209 | 20.0 4 130.0 102.0 3150. 15.7 76 2 "volvo 245" 210 | 13.0 8 318.0 150.0 3940. 13.2 76 1 "plymouth volare premier v8" 211 | 19.0 4 120.0 88.00 3270. 21.9 76 2 "peugeot 504" 212 | 19.0 6 156.0 108.0 2930. 15.5 76 3 "toyota mark ii" 213 | 16.5 6 168.0 120.0 3820. 16.7 76 2 "mercedes-benz 280s" 214 | 16.5 8 350.0 180.0 4380. 12.1 76 1 "cadillac seville" 215 | 13.0 8 350.0 145.0 4055. 12.0 76 1 "chevy c10" 216 | 13.0 8 302.0 130.0 3870. 15.0 76 1 "ford f108" 217 | 13.0 8 318.0 150.0 3755. 14.0 76 1 "dodge d100" 218 | 31.5 4 98.00 68.00 2045. 18.5 77 3 "honda accord cvcc" 219 | 30.0 4 111.0 80.00 2155. 14.8 77 1 "buick opel isuzu deluxe" 220 | 36.0 4 79.00 58.00 1825. 18.6 77 2 "renault 5 gtl" 221 | 25.5 4 122.0 96.00 2300. 15.5 77 1 "plymouth arrow gs" 222 | 33.5 4 85.00 70.00 1945. 16.8 77 3 "datsun f-10 hatchback" 223 | 17.5 8 305.0 145.0 3880. 12.5 77 1 "chevrolet caprice classic" 224 | 17.0 8 260.0 110.0 4060. 19.0 77 1 "oldsmobile cutlass supreme" 225 | 15.5 8 318.0 145.0 4140. 13.7 77 1 "dodge monaco brougham" 226 | 15.0 8 302.0 130.0 4295. 14.9 77 1 "mercury cougar brougham" 227 | 17.5 6 250.0 110.0 3520. 16.4 77 1 "chevrolet concours" 228 | 20.5 6 231.0 105.0 3425. 16.9 77 1 "buick skylark" 229 | 19.0 6 225.0 100.0 3630. 17.7 77 1 "plymouth volare custom" 230 | 18.5 6 250.0 98.00 3525. 19.0 77 1 "ford granada" 231 | 16.0 8 400.0 180.0 4220. 11.1 77 1 "pontiac grand prix lj" 232 | 15.5 8 350.0 170.0 4165. 11.4 77 1 "chevrolet monte carlo landau" 233 | 15.5 8 400.0 190.0 4325. 12.2 77 1 "chrysler cordoba" 234 | 16.0 8 351.0 149.0 4335. 14.5 77 1 "ford thunderbird" 235 | 29.0 4 97.00 78.00 1940. 14.5 77 2 "volkswagen rabbit custom" 236 | 24.5 4 151.0 88.00 2740. 16.0 77 1 "pontiac sunbird coupe" 237 | 26.0 4 97.00 75.00 2265. 18.2 77 3 "toyota corolla liftback" 238 | 25.5 4 140.0 89.00 2755. 15.8 77 1 "ford mustang ii 2+2" 239 | 30.5 4 98.00 63.00 2051. 17.0 77 1 "chevrolet chevette" 240 | 33.5 4 98.00 83.00 2075. 15.9 77 1 "dodge colt m/m" 241 | 30.0 4 97.00 67.00 1985. 16.4 77 3 "subaru dl" 242 | 30.5 4 97.00 78.00 2190. 14.1 77 2 "volkswagen dasher" 243 | 22.0 6 146.0 97.00 2815. 14.5 77 3 "datsun 810" 244 | 21.5 4 121.0 110.0 2600. 12.8 77 2 "bmw 320i" 245 | 21.5 3 80.00 110.0 2720. 13.5 77 3 "mazda rx-4" 246 | 43.1 4 90.00 48.00 1985. 21.5 78 2 "volkswagen rabbit custom diesel" 247 | 36.1 4 98.00 66.00 1800. 14.4 78 1 "ford fiesta" 248 | 32.8 4 78.00 52.00 1985. 19.4 78 3 "mazda glc deluxe" 249 | 39.4 4 85.00 70.00 2070. 18.6 78 3 "datsun b210 gx" 250 | 36.1 4 91.00 60.00 1800. 16.4 78 3 "honda civic cvcc" 251 | 19.9 8 260.0 110.0 3365. 15.5 78 1 "oldsmobile cutlass salon brougham" 252 | 19.4 8 318.0 140.0 3735. 13.2 78 1 "dodge diplomat" 253 | 20.2 8 302.0 139.0 3570. 12.8 78 1 "mercury monarch ghia" 254 | 19.2 6 231.0 105.0 3535. 19.2 78 1 "pontiac phoenix lj" 255 | 20.5 6 200.0 95.00 3155. 18.2 78 1 "chevrolet malibu" 256 | 20.2 6 200.0 85.00 2965. 15.8 78 1 "ford fairmont (auto)" 257 | 25.1 4 140.0 88.00 2720. 15.4 78 1 "ford fairmont (man)" 258 | 20.5 6 225.0 100.0 3430. 17.2 78 1 "plymouth volare" 259 | 19.4 6 232.0 90.00 3210. 17.2 78 1 "amc concord" 260 | 20.6 6 231.0 105.0 3380. 15.8 78 1 "buick century special" 261 | 20.8 6 200.0 85.00 3070. 16.7 78 1 "mercury zephyr" 262 | 18.6 6 225.0 110.0 3620. 18.7 78 1 "dodge aspen" 263 | 18.1 6 258.0 120.0 3410. 15.1 78 1 "amc concord d/l" 264 | 19.2 8 305.0 145.0 3425. 13.2 78 1 "chevrolet monte carlo landau" 265 | 17.7 6 231.0 165.0 3445. 13.4 78 1 "buick regal sport coupe (turbo)" 266 | 18.1 8 302.0 139.0 3205. 11.2 78 1 "ford futura" 267 | 17.5 8 318.0 140.0 4080. 13.7 78 1 "dodge magnum xe" 268 | 30.0 4 98.00 68.00 2155. 16.5 78 1 "chevrolet chevette" 269 | 27.5 4 134.0 95.00 2560. 14.2 78 3 "toyota corona" 270 | 27.2 4 119.0 97.00 2300. 14.7 78 3 "datsun 510" 271 | 30.9 4 105.0 75.00 2230. 14.5 78 1 "dodge omni" 272 | 21.1 4 134.0 95.00 2515. 14.8 78 3 "toyota celica gt liftback" 273 | 23.2 4 156.0 105.0 2745. 16.7 78 1 "plymouth sapporo" 274 | 23.8 4 151.0 85.00 2855. 17.6 78 1 "oldsmobile starfire sx" 275 | 23.9 4 119.0 97.00 2405. 14.9 78 3 "datsun 200-sx" 276 | 20.3 5 131.0 103.0 2830. 15.9 78 2 "audi 5000" 277 | 17.0 6 163.0 125.0 3140. 13.6 78 2 "volvo 264gl" 278 | 21.6 4 121.0 115.0 2795. 15.7 78 2 "saab 99gle" 279 | 16.2 6 163.0 133.0 3410. 15.8 78 2 "peugeot 604sl" 280 | 31.5 4 89.00 71.00 1990. 14.9 78 2 "volkswagen scirocco" 281 | 29.5 4 98.00 68.00 2135. 16.6 78 3 "honda accord lx" 282 | 21.5 6 231.0 115.0 3245. 15.4 79 1 "pontiac lemans v6" 283 | 19.8 6 200.0 85.00 2990. 18.2 79 1 "mercury zephyr 6" 284 | 22.3 4 140.0 88.00 2890. 17.3 79 1 "ford fairmont 4" 285 | 20.2 6 232.0 90.00 3265. 18.2 79 1 "amc concord dl 6" 286 | 20.6 6 225.0 110.0 3360. 16.6 79 1 "dodge aspen 6" 287 | 17.0 8 305.0 130.0 3840. 15.4 79 1 "chevrolet caprice classic" 288 | 17.6 8 302.0 129.0 3725. 13.4 79 1 "ford ltd landau" 289 | 16.5 8 351.0 138.0 3955. 13.2 79 1 "mercury grand marquis" 290 | 18.2 8 318.0 135.0 3830. 15.2 79 1 "dodge st. regis" 291 | 16.9 8 350.0 155.0 4360. 14.9 79 1 "buick estate wagon (sw)" 292 | 15.5 8 351.0 142.0 4054. 14.3 79 1 "ford country squire (sw)" 293 | 19.2 8 267.0 125.0 3605. 15.0 79 1 "chevrolet malibu classic (sw)" 294 | 18.5 8 360.0 150.0 3940. 13.0 79 1 "chrysler lebaron town @ country (sw)" 295 | 31.9 4 89.00 71.00 1925. 14.0 79 2 "vw rabbit custom" 296 | 34.1 4 86.00 65.00 1975. 15.2 79 3 "maxda glc deluxe" 297 | 35.7 4 98.00 80.00 1915. 14.4 79 1 "dodge colt hatchback custom" 298 | 27.4 4 121.0 80.00 2670. 15.0 79 1 "amc spirit dl" 299 | 25.4 5 183.0 77.00 3530. 20.1 79 2 "mercedes benz 300d" 300 | 23.0 8 350.0 125.0 3900. 17.4 79 1 "cadillac eldorado" 301 | 27.2 4 141.0 71.00 3190. 24.8 79 2 "peugeot 504" 302 | 23.9 8 260.0 90.00 3420. 22.2 79 1 "oldsmobile cutlass salon brougham" 303 | 34.2 4 105.0 70.00 2200. 13.2 79 1 "plymouth horizon" 304 | 34.5 4 105.0 70.00 2150. 14.9 79 1 "plymouth horizon tc3" 305 | 31.8 4 85.00 65.00 2020. 19.2 79 3 "datsun 210" 306 | 37.3 4 91.00 69.00 2130. 14.7 79 2 "fiat strada custom" 307 | 28.4 4 151.0 90.00 2670. 16.0 79 1 "buick skylark limited" 308 | 28.8 6 173.0 115.0 2595. 11.3 79 1 "chevrolet citation" 309 | 26.8 6 173.0 115.0 2700. 12.9 79 1 "oldsmobile omega brougham" 310 | 33.5 4 151.0 90.00 2556. 13.2 79 1 "pontiac phoenix" 311 | 41.5 4 98.00 76.00 2144. 14.7 80 2 "vw rabbit" 312 | 38.1 4 89.00 60.00 1968. 18.8 80 3 "toyota corolla tercel" 313 | 32.1 4 98.00 70.00 2120. 15.5 80 1 "chevrolet chevette" 314 | 37.2 4 86.00 65.00 2019. 16.4 80 3 "datsun 310" 315 | 28.0 4 151.0 90.00 2678. 16.5 80 1 "chevrolet citation" 316 | 26.4 4 140.0 88.00 2870. 18.1 80 1 "ford fairmont" 317 | 24.3 4 151.0 90.00 3003. 20.1 80 1 "amc concord" 318 | 19.1 6 225.0 90.00 3381. 18.7 80 1 "dodge aspen" 319 | 34.3 4 97.00 78.00 2188. 15.8 80 2 "audi 4000" 320 | 29.8 4 134.0 90.00 2711. 15.5 80 3 "toyota corona liftback" 321 | 31.3 4 120.0 75.00 2542. 17.5 80 3 "mazda 626" 322 | 37.0 4 119.0 92.00 2434. 15.0 80 3 "datsun 510 hatchback" 323 | 32.2 4 108.0 75.00 2265. 15.2 80 3 "toyota corolla" 324 | 46.6 4 86.00 65.00 2110. 17.9 80 3 "mazda glc" 325 | 27.9 4 156.0 105.0 2800. 14.4 80 1 "dodge colt" 326 | 40.8 4 85.00 65.00 2110. 19.2 80 3 "datsun 210" 327 | 44.3 4 90.00 48.00 2085. 21.7 80 2 "vw rabbit c (diesel)" 328 | 43.4 4 90.00 48.00 2335. 23.7 80 2 "vw dasher (diesel)" 329 | 36.4 5 121.0 67.00 2950. 19.9 80 2 "audi 5000s (diesel)" 330 | 30.0 4 146.0 67.00 3250. 21.8 80 2 "mercedes-benz 240d" 331 | 44.6 4 91.00 67.00 1850. 13.8 80 3 "honda civic 1500 gl" 332 | 40.9 4 85.00 ? 1835. 17.3 80 2 "renault lecar deluxe" 333 | 33.8 4 97.00 67.00 2145. 18.0 80 3 "subaru dl" 334 | 29.8 4 89.00 62.00 1845. 15.3 80 2 "vokswagen rabbit" 335 | 32.7 6 168.0 132.0 2910. 11.4 80 3 "datsun 280-zx" 336 | 23.7 3 70.00 100.0 2420. 12.5 80 3 "mazda rx-7 gs" 337 | 35.0 4 122.0 88.00 2500. 15.1 80 2 "triumph tr7 coupe" 338 | 23.6 4 140.0 ? 2905. 14.3 80 1 "ford mustang cobra" 339 | 32.4 4 107.0 72.00 2290. 17.0 80 3 "honda accord" 340 | 27.2 4 135.0 84.00 2490. 15.7 81 1 "plymouth reliant" 341 | 26.6 4 151.0 84.00 2635. 16.4 81 1 "buick skylark" 342 | 25.8 4 156.0 92.00 2620. 14.4 81 1 "dodge aries wagon (sw)" 343 | 23.5 6 173.0 110.0 2725. 12.6 81 1 "chevrolet citation" 344 | 30.0 4 135.0 84.00 2385. 12.9 81 1 "plymouth reliant" 345 | 39.1 4 79.00 58.00 1755. 16.9 81 3 "toyota starlet" 346 | 39.0 4 86.00 64.00 1875. 16.4 81 1 "plymouth champ" 347 | 35.1 4 81.00 60.00 1760. 16.1 81 3 "honda civic 1300" 348 | 32.3 4 97.00 67.00 2065. 17.8 81 3 "subaru" 349 | 37.0 4 85.00 65.00 1975. 19.4 81 3 "datsun 210 mpg" 350 | 37.7 4 89.00 62.00 2050. 17.3 81 3 "toyota tercel" 351 | 34.1 4 91.00 68.00 1985. 16.0 81 3 "mazda glc 4" 352 | 34.7 4 105.0 63.00 2215. 14.9 81 1 "plymouth horizon 4" 353 | 34.4 4 98.00 65.00 2045. 16.2 81 1 "ford escort 4w" 354 | 29.9 4 98.00 65.00 2380. 20.7 81 1 "ford escort 2h" 355 | 33.0 4 105.0 74.00 2190. 14.2 81 2 "volkswagen jetta" 356 | 34.5 4 100.0 ? 2320. 15.8 81 2 "renault 18i" 357 | 33.7 4 107.0 75.00 2210. 14.4 81 3 "honda prelude" 358 | 32.4 4 108.0 75.00 2350. 16.8 81 3 "toyota corolla" 359 | 32.9 4 119.0 100.0 2615. 14.8 81 3 "datsun 200sx" 360 | 31.6 4 120.0 74.00 2635. 18.3 81 3 "mazda 626" 361 | 28.1 4 141.0 80.00 3230. 20.4 81 2 "peugeot 505s turbo diesel" 362 | 30.7 6 145.0 76.00 3160. 19.6 81 2 "volvo diesel" 363 | 25.4 6 168.0 116.0 2900. 12.6 81 3 "toyota cressida" 364 | 24.2 6 146.0 120.0 2930. 13.8 81 3 "datsun 810 maxima" 365 | 22.4 6 231.0 110.0 3415. 15.8 81 1 "buick century" 366 | 26.6 8 350.0 105.0 3725. 19.0 81 1 "oldsmobile cutlass ls" 367 | 20.2 6 200.0 88.00 3060. 17.1 81 1 "ford granada gl" 368 | 17.6 6 225.0 85.00 3465. 16.6 81 1 "chrysler lebaron salon" 369 | 28.0 4 112.0 88.00 2605. 19.6 82 1 "chevrolet cavalier" 370 | 27.0 4 112.0 88.00 2640. 18.6 82 1 "chevrolet cavalier wagon" 371 | 34.0 4 112.0 88.00 2395. 18.0 82 1 "chevrolet cavalier 2-door" 372 | 31.0 4 112.0 85.00 2575. 16.2 82 1 "pontiac j2000 se hatchback" 373 | 29.0 4 135.0 84.00 2525. 16.0 82 1 "dodge aries se" 374 | 27.0 4 151.0 90.00 2735. 18.0 82 1 "pontiac phoenix" 375 | 24.0 4 140.0 92.00 2865. 16.4 82 1 "ford fairmont futura" 376 | 36.0 4 105.0 74.00 1980. 15.3 82 2 "volkswagen rabbit l" 377 | 37.0 4 91.00 68.00 2025. 18.2 82 3 "mazda glc custom l" 378 | 31.0 4 91.00 68.00 1970. 17.6 82 3 "mazda glc custom" 379 | 38.0 4 105.0 63.00 2125. 14.7 82 1 "plymouth horizon miser" 380 | 36.0 4 98.00 70.00 2125. 17.3 82 1 "mercury lynx l" 381 | 36.0 4 120.0 88.00 2160. 14.5 82 3 "nissan stanza xe" 382 | 36.0 4 107.0 75.00 2205. 14.5 82 3 "honda accord" 383 | 34.0 4 108.0 70.00 2245 16.9 82 3 "toyota corolla" 384 | 38.0 4 91.00 67.00 1965. 15.0 82 3 "honda civic" 385 | 32.0 4 91.00 67.00 1965. 15.7 82 3 "honda civic (auto)" 386 | 38.0 4 91.00 67.00 1995. 16.2 82 3 "datsun 310 gx" 387 | 25.0 6 181.0 110.0 2945. 16.4 82 1 "buick century limited" 388 | 38.0 6 262.0 85.00 3015. 17.0 82 1 "oldsmobile cutlass ciera (diesel)" 389 | 26.0 4 156.0 92.00 2585. 14.5 82 1 "chrysler lebaron medallion" 390 | 22.0 6 232.0 112.0 2835 14.7 82 1 "ford granada l" 391 | 32.0 4 144.0 96.00 2665. 13.9 82 3 "toyota celica gt" 392 | 36.0 4 135.0 84.00 2370. 13.0 82 1 "dodge charger 2.2" 393 | 27.0 4 151.0 90.00 2950. 17.3 82 1 "chevrolet camaro" 394 | 27.0 4 140.0 86.00 2790. 15.6 82 1 "ford mustang gl" 395 | 44.0 4 97.00 52.00 2130. 24.6 82 2 "vw pickup" 396 | 32.0 4 135.0 84.00 2295. 11.6 82 1 "dodge rampage" 397 | 28.0 4 120.0 79.00 2625. 18.6 82 1 "ford ranger" 398 | 31.0 4 119.0 82.00 2720. 19.4 82 1 "chevy s-10" 399 | -------------------------------------------------------------------------------- /Data/College.csv: -------------------------------------------------------------------------------- 1 | ,Private,Apps,Accept,Enroll,Top10perc,Top25perc,F.Undergrad,P.Undergrad,Outstate,Room.Board,Books,Personal,PhD,Terminal,S.F.Ratio,perc.alumni,Expend,Grad.Rate 2 | Abilene Christian University,Yes,1660,1232,721,23,52,2885,537,7440,3300,450,2200,70,78,18.1,12,7041,60 3 | Adelphi University,Yes,2186,1924,512,16,29,2683,1227,12280,6450,750,1500,29,30,12.2,16,10527,56 4 | Adrian College,Yes,1428,1097,336,22,50,1036,99,11250,3750,400,1165,53,66,12.9,30,8735,54 5 | Agnes Scott College,Yes,417,349,137,60,89,510,63,12960,5450,450,875,92,97,7.7,37,19016,59 6 | Alaska Pacific University,Yes,193,146,55,16,44,249,869,7560,4120,800,1500,76,72,11.9,2,10922,15 7 | Albertson College,Yes,587,479,158,38,62,678,41,13500,3335,500,675,67,73,9.4,11,9727,55 8 | Albertus Magnus College,Yes,353,340,103,17,45,416,230,13290,5720,500,1500,90,93,11.5,26,8861,63 9 | Albion College,Yes,1899,1720,489,37,68,1594,32,13868,4826,450,850,89,100,13.7,37,11487,73 10 | Albright College,Yes,1038,839,227,30,63,973,306,15595,4400,300,500,79,84,11.3,23,11644,80 11 | Alderson-Broaddus College,Yes,582,498,172,21,44,799,78,10468,3380,660,1800,40,41,11.5,15,8991,52 12 | Alfred University,Yes,1732,1425,472,37,75,1830,110,16548,5406,500,600,82,88,11.3,31,10932,73 13 | Allegheny College,Yes,2652,1900,484,44,77,1707,44,17080,4440,400,600,73,91,9.9,41,11711,76 14 | Allentown Coll. of St. Francis de Sales,Yes,1179,780,290,38,64,1130,638,9690,4785,600,1000,60,84,13.3,21,7940,74 15 | Alma College,Yes,1267,1080,385,44,73,1306,28,12572,4552,400,400,79,87,15.3,32,9305,68 16 | Alverno College,Yes,494,313,157,23,46,1317,1235,8352,3640,650,2449,36,69,11.1,26,8127,55 17 | American International College,Yes,1420,1093,220,9,22,1018,287,8700,4780,450,1400,78,84,14.7,19,7355,69 18 | Amherst College,Yes,4302,992,418,83,96,1593,5,19760,5300,660,1598,93,98,8.4,63,21424,100 19 | Anderson University,Yes,1216,908,423,19,40,1819,281,10100,3520,550,1100,48,61,12.1,14,7994,59 20 | Andrews University,Yes,1130,704,322,14,23,1586,326,9996,3090,900,1320,62,66,11.5,18,10908,46 21 | Angelo State University,No,3540,2001,1016,24,54,4190,1512,5130,3592,500,2000,60,62,23.1,5,4010,34 22 | Antioch University,Yes,713,661,252,25,44,712,23,15476,3336,400,1100,69,82,11.3,35,42926,48 23 | Appalachian State University,No,7313,4664,1910,20,63,9940,1035,6806,2540,96,2000,83,96,18.3,14,5854,70 24 | Aquinas College,Yes,619,516,219,20,51,1251,767,11208,4124,350,1615,55,65,12.7,25,6584,65 25 | Arizona State University Main campus,No,12809,10308,3761,24,49,22593,7585,7434,4850,700,2100,88,93,18.9,5,4602,48 26 | Arkansas College (Lyon College),Yes,708,334,166,46,74,530,182,8644,3922,500,800,79,88,12.6,24,14579,54 27 | Arkansas Tech University,No,1734,1729,951,12,52,3602,939,3460,2650,450,1000,57,60,19.6,5,4739,48 28 | Assumption College,Yes,2135,1700,491,23,59,1708,689,12000,5920,500,500,93,93,13.8,30,7100,88 29 | Auburn University-Main Campus,No,7548,6791,3070,25,57,16262,1716,6300,3933,600,1908,85,91,16.7,18,6642,69 30 | Augsburg College,Yes,662,513,257,12,30,2074,726,11902,4372,540,950,65,65,12.8,31,7836,58 31 | Augustana College IL,Yes,1879,1658,497,36,69,1950,38,13353,4173,540,821,78,83,12.7,40,9220,71 32 | Augustana College,Yes,761,725,306,21,58,1337,300,10990,3244,600,1021,66,70,10.4,30,6871,69 33 | Austin College,Yes,948,798,295,42,74,1120,15,11280,4342,400,1150,81,95,13,33,11361,71 34 | Averett College,Yes,627,556,172,16,40,777,538,9925,4135,750,1350,59,67,22.4,11,6523,48 35 | Baker University,Yes,602,483,206,21,47,958,466,8620,4100,400,2250,58,68,11,21,6136,65 36 | Baldwin-Wallace College,Yes,1690,1366,662,30,61,2718,1460,10995,4410,1000,1000,68,74,17.6,20,8086,85 37 | Barat College,Yes,261,192,111,15,36,453,266,9690,4300,500,500,57,77,9.7,35,9337,71 38 | Bard College,Yes,1910,838,285,50,85,1004,15,19264,6206,750,750,98,98,10.4,30,13894,79 39 | Barnard College,Yes,2496,1402,531,53,95,2121,69,17926,8124,600,850,83,93,10.3,33,12580,91 40 | Barry University,Yes,990,784,279,18,45,1811,3144,11290,5360,600,1800,76,78,12.6,11,9084,72 41 | Baylor University,Yes,6075,5349,2367,34,66,9919,484,6450,3920,600,1346,71,76,18.5,38,7503,72 42 | Beaver College,Yes,1163,850,348,23,56,878,519,12850,5400,400,800,78,89,12.2,30,8954,73 43 | Bellarmine College,Yes,807,707,308,39,63,1198,605,8840,2950,750,1290,74,82,13.1,31,6668,84 44 | Belmont Abbey College,Yes,632,494,129,17,36,709,131,9000,4850,300,2480,78,85,13.2,10,7550,52 45 | Belmont University,Yes,1220,974,481,28,67,1964,623,7800,3664,650,900,61,61,11.1,19,7614,49 46 | Beloit College,Yes,1320,923,284,26,54,1085,81,16304,3616,355,715,87,95,11.1,26,12957,69 47 | Bemidji State University,No,1208,877,546,12,36,3796,824,4425,2700,660,1800,57,62,19.6,16,3752,46 48 | Benedictine College,Yes,632,620,222,14,24,702,501,9550,3850,350,250,64,84,14.1,18,5922,58 49 | Bennington College,Yes,519,327,114,25,53,457,2,21700,4100,600,500,35,59,10.1,33,16364,55 50 | Bentley College,Yes,3466,2330,640,20,60,3095,1533,13800,5510,630,850,87,87,17.5,20,10941,82 51 | Berry College,Yes,1858,1221,480,37,68,1620,49,8050,3940,350,2375,80,80,16.3,17,10511,63 52 | Bethany College,Yes,878,816,200,16,41,706,62,8740,3363,550,1700,62,68,11.6,29,7718,48 53 | Bethel College KS,Yes,202,184,122,19,42,537,101,8540,3580,500,1400,61,80,8.8,32,8324,56 54 | Bethel College,Yes,502,384,104,11,28,347,74,6200,2900,600,800,63,63,11.7,13,7623,35 55 | Bethune Cookman College,Yes,1646,1150,542,12,30,2128,82,5188,3396,650,2500,48,48,13.8,9,6817,58 56 | Birmingham-Southern College,Yes,805,588,287,67,88,1376,207,11660,4325,400,900,74,79,14,34,8649,72 57 | Blackburn College,Yes,500,336,156,25,55,421,27,6500,2700,500,1000,76,76,14.3,53,8377,51 58 | Bloomsburg Univ. of Pennsylvania,No,6773,3028,1025,15,55,5847,946,7844,2948,500,1680,66,68,18,19,7041,75 59 | Bluefield College,Yes,377,358,181,15,30,653,129,7150,4350,450,1500,61,67,17.8,3,6259,53 60 | Bluffton College,Yes,692,514,209,20,50,760,81,9900,3990,400,900,76,71,13.3,19,9073,58 61 | Boston University,Yes,20192,13007,3810,45,80,14971,3113,18420,6810,475,1025,80,81,11.9,16,16836,72 62 | Bowdoin College,Yes,3356,1019,418,76,100,1490,8,19030,5885,1495,875,93,96,11.2,52,20447,96 63 | Bowling Green State University,No,9251,7333,3076,14,45,13699,1213,7452,3352,600,1700,81,89,21.1,14,6918,67 64 | Bradford College,Yes,443,330,151,5,36,453,42,14080,6270,500,900,57,80,10.2,21,15387,46 65 | Bradley University,Yes,3767,3414,1061,30,58,4531,643,10870,4440,2000,1522,75,81,14.4,21,7671,85 66 | Brandeis University,Yes,4186,2743,740,48,77,2819,62,19380,6750,410,1000,90,97,9.8,24,17150,84 67 | Brenau University,Yes,367,274,158,12,41,917,479,9592,5879,500,700,71,80,13.7,12,5935,49 68 | Brewton-Parker College,Yes,1436,1228,1202,10,26,1320,822,4371,2370,500,2000,62,62,12.6,10,4900,18 69 | Briar Cliff College,Yes,392,351,155,16,44,738,430,10260,3597,600,1500,39,66,13.1,26,8355,58 70 | Bridgewater College,Yes,838,673,292,22,53,881,55,10265,4725,560,875,68,73,13.2,24,8655,82 71 | Brigham Young University at Provo,Yes,7365,5402,4615,48,82,27378,1253,2340,3580,860,1220,76,76,20.5,40,7916,33 72 | Brown University,Yes,12586,3239,1462,87,95,5643,349,19528,5926,720,1100,99,100,7.6,39,20440,97 73 | Bryn Mawr College,Yes,1465,810,313,71,95,1088,16,18165,6750,500,1200,100,100,12.3,49,17449,89 74 | Bucknell University,Yes,6548,3813,862,49,85,3316,31,18550,4750,800,1200,95,97,14.2,36,13675,93 75 | Buena Vista College,Yes,860,688,285,32,70,1928,442,13306,3797,450,950,62,69,8.8,10,6333,78 76 | Butler University,Yes,2362,2037,700,40,68,2607,148,13130,4650,500,1600,77,81,10.9,29,9511,83 77 | Cabrini College,Yes,599,494,224,8,28,1035,446,10518,6250,300,300,59,76,16.5,36,7117,71 78 | Caldwell College,Yes,1011,604,213,17,42,693,868,8900,4600,425,1000,87,96,13.9,25,7922,55 79 | California Lutheran University,Yes,563,247,247,23,52,1427,432,12950,5300,612,576,72,74,12.4,17,8985,60 80 | California Polytechnic-San Luis,No,7811,3817,1650,47,73,12911,1404,7380,4877,612,2091,72,81,19.8,13,8453,59 81 | California State University at Fresno,No,4540,3294,1483,5,60,13494,1254,7706,4368,600,1926,90,90,21.2,8,7268,61 82 | Calvin College,Yes,1784,1512,913,29,56,3401,136,10230,3710,400,1210,75,81,14.8,41,7786,81 83 | Campbell University,Yes,2087,1339,657,20,54,3191,1204,7550,2790,600,500,77,77,21.8,34,3739,63 84 | Campbellsville College,Yes,848,587,298,25,55,935,184,6060,3070,600,1300,62,66,17.7,13,5391,49 85 | Canisius College,Yes,2853,2193,753,16,34,2978,434,10750,5340,400,1130,90,92,14.6,26,7972,64 86 | Capital University,Yes,1747,1382,449,34,66,1662,960,13050,4000,500,800,64,69,12.1,27,9557,83 87 | Capitol College,Yes,100,90,35,10,52,282,331,8400,2812,300,2134,10,50,12.1,24,7976,52 88 | Carleton College,Yes,2694,1579,489,75,93,1870,12,19292,3957,550,550,81,93,10.4,60,17960,91 89 | Carnegie Mellon University,Yes,8728,5201,1191,60,89,4265,291,17900,5690,450,1250,86,93,9.2,31,24386,74 90 | Carroll College,Yes,1160,991,352,19,55,1357,737,12200,3880,480,930,74,81,17.8,25,7666,79 91 | Carson-Newman College,Yes,1096,951,464,27,62,1776,239,8150,3150,400,500,61,62,13.6,16,6716,67 92 | Carthage College,Yes,1616,1427,434,20,43,1405,580,13125,3775,500,1300,74,89,15.9,22,7364,62 93 | Case Western Reserve University,Yes,3877,3156,713,71,93,3051,513,15700,4730,525,1460,95,95,2.9,29,19733,67 94 | Castleton State College,No,1257,940,363,9,22,1547,294,7656,4690,400,700,89,91,14.7,8,6318,79 95 | Catawba College,Yes,1083,880,291,13,34,915,80,9270,4100,600,1860,75,82,13.5,27,8425,55 96 | Catholic University of America,Yes,1754,1465,505,24,49,2159,211,13712,6408,526,1100,90,96,9.3,18,12751,75 97 | Cazenovia College,Yes,3847,3433,527,9,35,1010,12,9384,4840,600,500,22,47,14.3,20,7697,118 98 | Cedar Crest College,Yes,776,607,198,25,58,791,764,14340,5285,500,1000,58,83,11.7,39,10961,74 99 | Cedarville College,Yes,1307,1090,616,25,55,2196,82,7344,4410,570,1000,50,52,15.3,34,6897,64 100 | Centenary College,Yes,369,312,90,12,46,396,526,11400,5400,500,760,41,85,9.5,20,9583,24 101 | Centenary College of Louisiana,Yes,495,434,210,35,55,775,44,8950,3490,600,1900,86,92,11.3,25,9685,66 102 | Center for Creative Studies,Yes,601,396,203,1,20,525,323,11230,6643,2340,620,8,58,6.8,4,13025,47 103 | Central College,Yes,1283,1113,401,31,65,1355,40,10938,3660,650,600,76,90,13.5,29,8444,67 104 | Central Connecticut State University,No,4158,2532,902,6,24,6394,3881,5962,4444,500,985,69,73,16.7,4,4900,49 105 | Central Missouri State University,No,4681,4101,1436,10,35,8094,1596,4620,3288,300,2250,69,80,19.7,4,5501,50 106 | Central Washington University,No,2785,2011,1007,8,65,6507,898,7242,3603,654,1416,67,89,18.1,0,6413,51 107 | Central Wesleyan College,Yes,174,146,88,8,29,1047,33,8300,3080,600,600,62,62,15.2,18,3365,58 108 | Centre College,Yes,1013,888,288,55,82,943,7,11850,4270,600,900,95,99,11.4,60,13118,74 109 | Chapman University,Yes,959,771,351,23,48,1662,209,16624,5895,600,1100,72,80,12.8,6,12692,47 110 | Chatham College,Yes,212,197,91,28,56,471,148,13500,5230,400,850,95,98,9.3,37,16095,52 111 | Chestnut Hill College,Yes,342,254,126,25,64,518,232,10335,5015,700,850,71,71,8.3,29,7729,73 112 | Christendom College,Yes,81,72,51,33,71,139,3,8730,3600,400,800,92,92,9.3,17,10922,58 113 | Christian Brothers University,Yes,880,520,224,16,42,1068,364,9300,3260,600,900,81,81,11.1,24,8129,63 114 | Christopher Newport University,No,883,766,428,3,37,2910,1749,7860,4750,525,1889,80,82,21.2,16,4639,48 115 | Claflin College,Yes,1196,697,499,21,47,959,13,4412,2460,500,1000,69,69,16.9,31,7083,21 116 | Claremont McKenna College,Yes,1860,767,227,71,93,887,1,17000,6010,500,850,99,99,9.6,52,18443,87 117 | Clark University,Yes,2887,2059,457,30,61,1928,296,17500,4200,500,950,94,95,10.5,35,11951,79 118 | Clarke College,Yes,460,340,167,14,45,604,350,10740,3676,350,900,67,71,11,27,7963,74 119 | Clarkson University,Yes,2174,1953,557,35,68,2332,53,15960,5580,700,1300,95,95,15.8,32,11659,77 120 | Clemson University,No,8065,5257,2301,37,65,11755,770,8116,3610,800,1618,82,88,18,17,7597,73 121 | Clinch Valley Coll. of the Univ. of Virginia,No,689,561,250,15,30,1125,422,7168,3689,600,1900,67,67,18.1,9,4417,46 122 | Coe College,Yes,1006,742,275,29,60,1127,205,13925,4390,500,2200,73,86,12.7,32,10141,67 123 | Coker College,Yes,604,452,295,15,47,690,222,9888,4502,400,1000,64,77,12.1,39,8741,75 124 | Colby College,Yes,2848,1319,456,58,84,1720,35,18930,5590,500,1000,83,94,10.2,41,15954,91 125 | Colgate University,Yes,4856,2492,727,46,75,2649,25,19510,5565,500,750,95,98,10.5,45,15494,93 126 | College Misericordia,Yes,1432,888,317,29,58,1121,493,10860,5760,550,900,56,62,12.9,23,8604,96 127 | College of Charleston,No,4772,3140,1265,22,55,6851,1200,6120,3460,666,2316,73,78,17.2,18,4776,51 128 | College of Mount St. Joseph,Yes,798,620,238,14,41,1165,1232,9800,4430,400,1150,46,46,11.1,35,6889,100 129 | College of Mount St. Vincent,Yes,946,648,177,23,46,707,432,11790,5770,500,1000,75,77,11.9,35,10015,83 130 | College of Notre Dame,Yes,344,264,97,11,42,500,331,12600,5520,630,2250,77,80,10.4,7,9773,43 131 | College of Notre Dame of Maryland,Yes,457,356,177,35,61,667,1983,11180,5620,600,700,64,64,11.5,32,7477,75 132 | College of Saint Benedict,Yes,938,864,511,29,62,1715,103,12247,4221,500,600,70,88,13.1,26,8847,72 133 | College of Saint Catherine,Yes,511,411,186,23,51,1692,562,12224,4440,450,1000,63,87,11.5,32,7315,77 134 | College of Saint Elizabeth,Yes,444,359,122,34,53,493,968,10900,5250,380,1000,68,70,11.4,23,9447,78 135 | College of Saint Rose,Yes,983,664,249,23,57,1698,894,9990,5666,800,1500,66,71,14.3,28,6084,64 136 | College of Santa Fe,Yes,546,447,189,16,42,873,683,11138,4138,600,1200,40,74,14,7,8820,80 137 | College of St. Joseph,Yes,141,118,55,12,21,201,173,8300,4850,450,1300,53,53,9.5,19,6936,76 138 | College of St. Scholastica,Yes,672,596,278,29,60,1350,275,11844,3696,450,1146,54,76,11.6,33,8996,72 139 | College of the Holy Cross,Yes,2994,1691,659,70,95,2675,22,18000,6300,400,900,92,96,11.3,55,12138,95 140 | College of William and Mary,No,7117,3106,1217,68,88,5186,134,11720,4298,600,800,89,92,12.1,31,9534,93 141 | College of Wooster,Yes,2100,1883,553,29,65,1704,1,16240,4690,500,500,84,96,11.1,43,14140,69 142 | Colorado College,Yes,3207,1577,490,56,87,1892,7,17142,4190,450,1200,85,97,11.3,51,14664,84 143 | Colorado State University,No,9478,6312,2194,29,65,15646,1829,8412,4180,470,1800,87,89,19.2,10,7850,59 144 | Columbia College MO,Yes,314,158,132,10,28,690,5346,8294,3700,400,900,87,87,15.3,2,5015,37 145 | Columbia College,Yes,737,614,242,21,67,968,237,10425,3975,500,1500,61,77,14.7,34,8693,76 146 | Columbia University,Yes,6756,1930,871,78,96,3376,55,18624,6664,550,300,97,98,5.9,21,30639,99 147 | Concordia College at St. Paul,Yes,281,266,139,13,29,1049,181,10500,3750,450,950,69,75,12.8,18,6955,45 148 | Concordia Lutheran College,Yes,232,216,106,16,34,534,172,6900,3800,450,1825,67,76,12.1,9,6875,42 149 | Concordia University CA,Yes,688,497,144,30,75,641,101,10800,4440,570,1515,55,60,13.1,13,8415,55 150 | Concordia University,Yes,528,403,186,22,56,1168,145,9216,4191,400,1000,56,64,12.1,13,7309,75 151 | Connecticut College,Yes,3035,1546,438,42,93,1630,232,18740,6300,600,500,86,95,10.7,40,14773,91 152 | Converse College,Yes,440,407,149,35,70,643,80,12050,3700,500,900,63,76,10.2,31,10965,75 153 | Cornell College,Yes,1538,1329,383,33,68,1140,10,15248,4323,550,800,71,76,12.2,31,10340,64 154 | Creighton University,Yes,2967,2836,876,30,60,3450,644,10628,4372,650,2055,85,90,6.5,32,22906,85 155 | Culver-Stockton College,Yes,1576,1110,274,24,55,992,112,8000,3700,400,500,51,52,14.1,28,5807,51 156 | Cumberland College,Yes,995,789,398,26,47,1306,122,6230,3526,400,600,42,44,13,4,8189,63 157 | D'Youville College,Yes,866,619,157,18,47,1074,336,8920,4310,680,1320,68,68,14.6,42,6898,46 158 | Dana College,Yes,504,482,185,10,36,550,84,9130,3322,450,1450,46,51,12.6,25,8686,54 159 | Daniel Webster College,Yes,585,508,153,12,30,460,536,12292,4934,500,500,61,61,22.2,10,8643,72 160 | Dartmouth College,Yes,8587,2273,1087,87,99,3918,32,19545,6070,550,1100,95,99,4.7,49,29619,98 161 | Davidson College,Yes,2373,956,452,77,96,1601,6,17295,5070,600,1011,95,97,12,46,17581,94 162 | Defiance College,Yes,571,461,174,10,26,645,283,10850,3670,400,1159,58,60,12.8,19,7505,56 163 | Delta State University,No,967,945,459,15,48,2806,538,4528,1880,500,1200,49,63,17.1,16,5113,58 164 | Denison University,Yes,2762,2279,533,32,60,1835,14,16900,4720,500,600,88,97,11.6,45,12423,81 165 | DePauw University,Yes,1994,1656,495,50,80,1983,36,14300,5020,550,950,78,94,11.1,31,11525,82 166 | Dickinson College,Yes,3014,2539,487,31,68,1889,62,18700,5000,595,1250,87,94,11.2,39,13861,87 167 | Dickinson State University,No,434,412,319,10,30,1376,237,4486,2146,600,2000,50,64,16.5,28,4525,46 168 | Dillard University,Yes,1998,1376,651,41,88,1539,45,6700,3650,500,2307,52,52,14.1,12,7566,61 169 | Doane College,Yes,793,709,244,20,47,1022,411,9570,3000,400,1000,67,72,15.1,42,6852,60 170 | Dominican College of Blauvelt,Yes,360,329,108,4,19,756,863,8310,5500,600,1800,43,43,12.7,5,5480,54 171 | Dordt College,Yes,604,562,328,25,50,1048,56,9800,2650,450,2800,61,60,12.5,17,7325,87 172 | Dowling College,Yes,1011,829,410,9,33,1059,2458,9000,3100,450,1413,77,78,12.4,7,11178,42 173 | Drake University,Yes,2799,2573,839,34,65,3322,726,13420,4770,560,1675,88,93,15,24,9473,77 174 | Drew University,Yes,2153,1580,321,56,84,1192,87,18432,5616,520,660,93,97,10.2,28,14907,83 175 | Drury College,Yes,700,650,314,33,66,1065,48,8730,3523,500,750,82,92,13.2,35,9303,67 176 | Duke University,Yes,13789,3893,1583,90,98,6188,53,18590,5950,625,1162,95,96,5,44,27206,97 177 | Earlham College,Yes,1358,1006,274,35,63,1028,13,15036,4056,600,600,90,94,10.6,46,14634,78 178 | East Carolina University,No,9274,6362,2435,14,44,13171,1687,7248,3240,500,1700,74,78,13.2,18,9002,58 179 | East Tennessee State University,No,3330,2730,1303,15,36,6706,2640,5800,3000,600,2200,73,75,14,9,9825,42 180 | East Texas Baptist University,Yes,379,341,265,10,36,1050,151,4950,2780,530,1500,62,62,15.7,7,5619,38 181 | Eastern College,Yes,458,369,165,16,42,1057,355,11190,4800,450,1230,60,60,13.6,22,8135,54 182 | Eastern Connecticut State University,No,2172,1493,564,14,50,2766,1531,5962,4316,650,500,71,76,16.9,14,5719,50 183 | Eastern Illinois University,No,5597,4253,1565,12,38,9161,845,5710,3066,120,1730,62,71,16.2,5,5682,76 184 | Eastern Mennonite College,Yes,486,440,227,19,48,903,59,9650,3800,600,1300,46,65,11.4,29,10188,82 185 | Eastern Nazarene College,Yes,516,409,200,17,40,1238,30,8770,3500,450,700,58,58,17.3,17,6430,70 186 | Eckerd College,Yes,1422,1109,366,33,65,1363,23,15360,4080,600,1000,82,89,12.8,26,15003,59 187 | Elizabethtown College,Yes,2417,1843,426,36,70,1476,299,14190,4400,500,750,65,68,12.8,25,9815,81 188 | Elmira College,Yes,1457,1045,345,27,50,1109,502,14990,4980,450,550,77,98,21.5,21,7502,64 189 | Elms College,Yes,245,208,125,23,46,544,436,11800,4765,450,1700,71,71,11.3,21,8952,86 190 | Elon College,Yes,3624,2786,858,11,39,2933,334,9100,3883,490,1777,70,74,18.9,34,6329,63 191 | Embry Riddle Aeronautical University,Yes,3151,2584,958,14,40,4772,856,7800,3750,570,3020,37,43,16.5,4,12878,44 192 | Emory & Henry College,Yes,765,646,226,30,60,809,32,8578,4408,700,1600,79,88,13.9,51,8061,82 193 | Emory University,Yes,8506,4168,1236,76,97,5544,192,17600,6000,600,870,97,98,5,28,28457,96 194 | Emporia State University,No,1256,1256,853,43,79,3957,588,5401,3144,450,1888,72,75,19.3,4,5527,50 195 | Erskine College,Yes,659,557,167,47,74,532,35,10485,3840,475,1246,76,80,13.5,47,7527,67 196 | Eureka College,Yes,560,454,113,36,56,484,16,10955,3450,330,670,62,87,10.6,31,9552,53 197 | Evergreen State College,No,1801,1101,438,14,50,3065,363,6297,4600,600,1323,75,78,18.1,14,8355,68 198 | Fairfield University,Yes,4784,3346,781,30,66,2984,1037,15000,6200,700,1100,86,90,15.1,30,11220,94 199 | Fayetteville State University,No,1455,1064,452,1,16,2632,617,6806,2550,350,766,75,75,15.1,10,6972,24 200 | Ferrum College,Yes,1339,1107,336,12,36,1051,82,9400,4200,500,1600,53,58,12.5,9,7967,22 201 | Flagler College,Yes,1415,714,338,18,52,1345,44,5120,3200,500,2140,52,60,18.1,9,3930,69 202 | Florida Institute of Technology,Yes,1947,1580,523,39,74,1863,233,13900,4140,750,1500,90,90,10.6,7,8923,57 203 | Florida International University,No,3306,2079,1071,42,89,10208,9310,6597,2494,800,3028,81,96,13.9,20,6722,66 204 | Florida Southern College,Yes,1381,1040,374,20,44,1506,970,8025,4865,400,650,65,74,17.4,10,6339,68 205 | Florida State University,No,11651,8683,3023,50,90,18906,3242,6680,4060,600,1020,80,89,23.1,15,7250,58 206 | Fontbonne College,Yes,291,245,126,16,49,981,337,8390,4100,350,1500,45,55,21.5,24,4607,62 207 | Fordham University,Yes,4200,2874,942,30,55,4740,1646,14235,6965,600,1735,86,97,14.4,14,10864,80 208 | Fort Lewis College,No,3440,2823,1123,16,35,3793,486,6198,3320,500,2500,89,97,19.1,6,4362,46 209 | Francis Marion University,No,1801,1655,819,13,38,3224,436,5840,3138,400,2430,76,76,19.1,8,5039,43 210 | Franciscan University of Steubenville,Yes,553,452,228,22,49,1301,242,9650,4400,600,1000,57,69,14.9,8,6336,83 211 | Franklin College,Yes,804,632,281,29,72,840,68,10390,4040,525,1345,54,78,12.5,37,11751,60 212 | Franklin Pierce College,Yes,5187,4471,446,3,14,1818,1197,13320,4630,500,800,50,56,17.6,16,6418,51 213 | Freed-Hardeman University,Yes,895,548,314,20,54,1174,50,5500,3340,600,1600,68,76,16.1,13,6078,62 214 | Fresno Pacific College,Yes,346,274,146,51,87,704,63,9900,3670,630,1818,59,59,10.5,14,8095,54 215 | Furman University,Yes,2161,1951,685,56,82,2371,175,13440,4048,600,1250,92,95,13.5,28,12940,82 216 | Gannon University,Yes,2464,1908,678,24,57,2693,691,10970,4280,500,1380,47,51,13.3,18,7711,65 217 | Gardner Webb University,Yes,1110,930,332,18,36,1603,374,8180,4270,500,500,65,58,15.2,12,5664,29 218 | Geneva College,Yes,668,534,237,19,39,1306,258,9476,4820,500,1100,67,67,20.1,26,6786,74 219 | George Fox College,Yes,809,726,294,27,52,1271,43,12500,4130,400,1050,53,53,13.5,22,7136,52 220 | George Mason University,No,5653,4326,1727,17,29,9528,3822,10800,4840,580,1050,93,96,19.3,7,6751,46 221 | George Washington University,Yes,7875,5062,1492,38,71,5471,1470,17450,6328,700,950,92,93,7.6,15,14745,72 222 | Georgetown College,Yes,727,693,286,30,55,1063,48,8100,3950,550,550,73,76,13.3,28,7508,55 223 | Georgetown University,Yes,11115,2881,1390,71,93,5881,406,18300,7131,670,1700,91,92,7.2,27,19635,95 224 | Georgia Institute of Technology,No,7837,4527,2276,89,99,8528,654,6489,4438,795,1164,92,92,19.3,33,11271,70 225 | Georgia State University,No,3793,2341,1238,9,24,7732,9054,6744,2655,720,3450,87,89,19,10,7762,34 226 | Georgian Court College,Yes,348,281,127,12,52,1095,785,9150,3950,500,800,56,59,12.2,27,7348,76 227 | Gettysburg College,Yes,3596,2466,575,42,78,1944,46,19964,4328,500,500,94,95,12.1,32,14720,83 228 | Goldey Beacom College,Yes,633,468,284,10,27,823,963,6120,2985,531,1830,25,25,27.6,4,6081,36 229 | Gonzaga University,Yes,1886,1524,526,31,67,2523,296,13000,4450,600,2400,78,90,14.7,32,9553,69 230 | Gordon College,Yes,674,565,282,25,54,1151,39,12200,4070,400,1200,73,82,14.2,32,9226,66 231 | Goshen College,Yes,440,396,221,26,51,910,166,9420,3730,600,1230,51,56,9.9,46,10270,72 232 | Goucher College,Yes,1151,813,248,40,64,850,80,15588,6174,500,1200,78,90,9.2,34,16623,77 233 | Grace College and Seminary,Yes,548,428,167,18,46,618,113,8958,3670,300,1000,53,59,15.3,26,9798,64 234 | Graceland College,Yes,555,414,242,14,41,996,2281,9100,3100,550,880,51,61,23.6,24,5609,47 235 | Grand Valley State University,No,5165,3887,1561,20,60,8234,2619,6108,3800,500,1000,64,66,20.6,9,5063,57 236 | Green Mountain College,Yes,780,628,198,7,20,545,42,11750,2700,400,850,77,83,14,24,6475,76 237 | Greensboro College,Yes,608,494,176,10,31,649,314,8330,3770,550,1300,64,80,13,31,7949,39 238 | Greenville College,Yes,510,387,194,20,46,771,53,10310,4530,400,800,57,61,14.3,16,8222,60 239 | Grinnell College,Yes,2039,1389,432,56,91,1333,30,15688,4618,400,400,88,92,9.5,54,18979,83 240 | Grove City College,Yes,2491,1110,573,57,88,2213,35,5224,3048,525,350,65,65,18.4,18,4957,100 241 | Guilford College,Yes,1202,1054,326,18,44,1410,299,13404,5160,450,1050,78,86,15.6,30,9114,65 242 | Gustavus Adolphus College,Yes,1709,1385,634,36,72,2281,50,14125,3600,400,700,79,89,12.5,58,9907,80 243 | Gwynedd Mercy College,Yes,380,237,104,30,56,716,1108,11000,5550,500,500,36,41,7.8,22,7483,96 244 | Hamilton College,Yes,3140,1783,454,40,82,1646,24,19700,5050,300,800,91,96,9.6,60,17761,91 245 | Hamline University,Yes,1006,825,328,34,73,1362,102,13252,4194,450,550,89,93,13,33,10296,65 246 | Hampden - Sydney College,Yes,817,644,307,20,40,945,1,13218,4773,660,600,95,97,13.3,53,12263,69 247 | Hampton University,Yes,7178,3755,1433,25,63,4623,740,7161,3518,600,2000,60,64,14,9,6791,70 248 | Hanover College,Yes,1006,837,317,33,65,1024,15,8200,3485,500,1200,84,84,10.6,26,9248,64 249 | Hardin-Simmons University,Yes,467,424,350,16,40,1365,334,6300,2980,700,2140,75,79,13.7,10,7054,38 250 | Harding University,Yes,1721,1068,806,35,75,3128,213,5504,3528,700,910,71,77,17.7,37,6466,73 251 | Hartwick College,Yes,2083,1725,430,22,49,1464,67,17480,4780,500,700,75,87,12.3,32,11625,73 252 | Harvard University,Yes,13865,2165,1606,90,100,6862,320,18485,6410,500,1920,97,97,9.9,52,37219,100 253 | Harvey Mudd College,Yes,1377,572,178,95,100,654,5,17230,6690,700,900,100,100,8.2,46,21569,100 254 | Hastings College,Yes,817,708,262,22,52,935,37,9376,3272,500,1902,57,63,13,17,7335,52 255 | Hendrix College,Yes,823,721,274,52,87,954,6,8800,3195,500,1200,82,99,13.1,26,8588,63 256 | Hillsdale College,Yes,920,745,347,35,66,1133,42,11090,4700,400,750,80,80,12,31,12639,79 257 | Hiram College,Yes,922,729,244,37,66,1000,275,14067,4560,400,1000,75,95,10.6,34,12165,79 258 | Hobart and William Smith Colleges,Yes,2688,2081,500,25,53,1792,5,19029,5841,600,600,99,99,12.1,37,13040,79 259 | Hofstra University,Yes,7428,5860,1349,25,63,6534,1350,11600,5920,1000,1000,81,90,13.9,10,10093,60 260 | Hollins College,Yes,602,498,215,26,58,795,74,13470,5515,500,850,78,91,11.1,48,13957,72 261 | Hood College,Yes,699,565,176,36,64,710,399,13960,6040,450,690,82,88,14.4,34,12434,72 262 | Hope College,Yes,1712,1483,624,37,69,2505,208,12275,4341,465,1100,72,81,12.5,40,9284,72 263 | Houghton College,Yes,949,786,302,30,70,1210,26,9990,3550,500,1500,85,90,15,24,8187,67 264 | Huntingdon College,Yes,608,520,127,26,47,538,126,8080,3920,500,1100,63,72,11.4,9,7703,44 265 | Huntington College,Yes,450,430,125,20,46,488,43,9950,3920,300,1300,76,76,11.8,25,9466,47 266 | Huron University,Yes,600,197,124,3,9,392,69,7260,3090,600,1840,31,35,12.9,4,9249,21 267 | Husson College,Yes,723,652,361,10,30,951,706,7800,4000,350,1500,36,44,22,4,4923,84 268 | Illinois Benedictine College,Yes,607,558,269,22,47,1222,519,10500,4348,650,1500,81,91,11.6,29,8324,75 269 | Illinois College,Yes,894,787,262,28,63,909,28,8050,3850,600,1000,75,75,15.6,30,7348,52 270 | Illinois Institute of Technology,Yes,1756,1360,478,42,77,1911,626,14550,4620,500,700,80,88,12.3,26,12851,56 271 | Illinois State University,No,8681,6695,2408,10,35,15701,1823,7799,3403,537,2605,77,84,21,16,5569,54 272 | Illinois Wesleyan University,Yes,3050,1342,471,55,86,1818,23,14360,4090,400,650,77,92,12.9,34,9605,83 273 | Immaculata College,Yes,268,253,103,16,44,494,1305,10000,5364,500,1000,56,64,11.2,33,7305,69 274 | Incarnate Word College,Yes,1163,927,386,16,49,1685,556,8840,4689,750,2775,67,69,11.4,21,6095,95 275 | Indiana State University,No,5659,4761,3147,10,31,8596,1949,6892,3706,600,2500,72,76,16.6,8,6996,40 276 | Indiana University at Bloomington,No,16587,13243,5873,25,72,24763,2717,9766,3990,600,2000,77,88,21.3,24,8686,68 277 | Indiana Wesleyan University,Yes,735,423,366,20,48,2448,707,9210,3782,700,1000,49,51,39.8,15,6562,34 278 | Iona College,Yes,4892,3530,913,13,33,3906,1446,10690,6790,570,1150,66,83,16,14,8107,66 279 | Iowa State University,No,8427,7424,3441,26,59,18676,1715,7550,3224,640,2055,81,88,19.2,22,8420,65 280 | Ithaca College,Yes,7259,5526,1368,23,52,5612,166,14424,6192,634,1000,58,79,11.5,25,9812,75 281 | James Madison University,No,11223,5285,2082,32,72,9652,742,7994,4544,500,732,77,81,17.9,29,5212,98 282 | Jamestown College,Yes,472,410,262,14,41,9950,71,7620,3050,400,400,51,53,17,21,3186,54 283 | Jersey City State College,No,2957,1423,691,10,30,3817,1394,3946,4800,400,1500,63,67,14.9,10,8367,26 284 | John Brown University,Yes,605,405,284,24,53,961,99,6398,3672,400,1350,68,68,13.3,19,8118,75 285 | John Carroll University,Yes,2421,2109,820,27,57,3168,392,11700,5550,600,450,89,90,14.5,28,7738,89 286 | Johns Hopkins University,Yes,8474,3446,911,75,94,3566,1569,18800,6740,500,1040,96,97,3.3,38,56233,90 287 | Johnson State College,No,833,669,279,3,13,1224,345,7656,4690,500,624,80,91,14.4,15,6564,36 288 | Judson College,Yes,313,228,137,10,30,552,67,9414,4554,500,1700,34,55,10.6,30,7840,56 289 | Juniata College,Yes,1005,859,298,36,55,1075,43,14850,4460,450,420,97,97,12.7,37,12067,80 290 | Kansas State University,No,5880,4075,2833,25,55,14914,2246,6995,3120,600,2000,76,86,18.5,22,6122,54 291 | Kansas Wesleyan University,Yes,589,575,148,16,40,474,258,8400,3250,500,1400,63,55,12.4,14,6535,68 292 | Keene State College,No,3121,2446,822,5,19,3480,776,7870,4157,500,1150,73,73,16.1,13,6195,61 293 | Kentucky Wesleyan College,Yes,584,497,175,20,49,662,121,8000,4150,500,1300,57,65,11.3,32,7058,62 294 | Kenyon College,Yes,2212,1538,408,44,75,1445,1,19240,3690,750,480,95,95,11.1,46,14067,88 295 | Keuka College,Yes,461,381,174,10,43,738,55,9600,4550,600,750,55,94,13.3,43,7863,51 296 | King's College,Yes,1456,1053,381,20,45,500,541,10910,5160,400,1795,66,72,15.6,37,7649,87 297 | King College,Yes,355,300,142,34,65,509,44,8664,3350,600,3000,65,68,10.7,25,8954,65 298 | Knox College,Yes,1040,845,286,48,77,967,24,15747,4062,400,800,88,95,12.7,33,13224,79 299 | La Roche College,Yes,361,321,185,10,41,650,819,8842,4782,600,1100,57,73,14.2,14,7022,52 300 | La Salle University,Yes,2929,1834,622,20,56,2738,1662,12600,5610,450,3160,90,90,15.1,9,9084,84 301 | Lafayette College,Yes,4010,2402,572,36,59,2018,226,18730,5740,600,1000,93,96,10.5,38,15365,92 302 | LaGrange College,Yes,544,399,177,15,35,600,363,6987,3585,750,1500,77,83,12.5,12,9067,75 303 | Lake Forest College,Yes,979,638,271,31,70,968,20,16880,3970,920,1320,91,94,10.7,19,15687,77 304 | Lakeland College,Yes,497,452,231,24,47,887,1957,9400,4005,500,1000,49,65,17.2,25,4054,57 305 | Lamar University,No,2336,1725,1043,10,27,5438,4058,4752,3040,508,1463,48,82,18.4,12,5879,26 306 | Lambuth University,Yes,831,538,224,15,35,840,325,5170,3430,600,1590,61,61,16.1,10,5531,60 307 | Lander University,No,1166,1009,510,9,33,2074,341,4938,2987,528,1702,67,77,17,11,6119,51 308 | Lawrence University,Yes,1243,947,324,50,77,1129,74,17163,3891,525,975,76,92,10.1,57,13965,77 309 | Le Moyne College,Yes,1470,1199,425,21,76,1820,558,11040,4840,400,900,89,92,13.3,28,8118,94 310 | Lebanon Valley College,Yes,1386,1060,320,28,56,965,502,13850,4755,400,1125,84,84,12.3,30,8196,85 311 | Lehigh University,Yes,6397,4304,1092,40,84,4298,132,18700,5580,750,1130,96,99,12.5,43,14665,91 312 | Lenoir-Rhyne College,Yes,979,743,259,25,46,1188,166,10100,4000,400,1000,88,92,12,20,8539,66 313 | Lesley College,Yes,244,198,82,12,33,1134,336,11700,5300,550,805,71,88,27.8,18,8694,58 314 | LeTourneau University,Yes,477,417,204,29,54,1532,77,8840,4240,600,1400,58,70,20.8,23,6863,56 315 | Lewis and Clark College,Yes,2774,2092,482,35,64,1763,59,15800,4790,450,950,97,98,12.3,21,12999,69 316 | Lewis University,Yes,1154,1050,395,12,31,2192,1423,10560,4520,500,1200,36,48,14.3,10,7701,61 317 | Lincoln Memorial University,Yes,787,562,363,21,55,925,605,5950,2890,600,1300,67,72,14.6,35,5177,53 318 | Lincoln University,No,1660,1091,326,15,41,1196,33,4818,3400,350,1400,71,72,12.6,8,10912,45 319 | Lindenwood College,Yes,810,484,356,6,33,2155,191,9200,4800,1000,4200,65,85,24.1,9,3480,100 320 | Linfield College,Yes,1561,1188,458,48,72,1548,840,13380,4210,500,900,89,91,17.8,34,8747,81 321 | Livingstone College,Yes,900,473,217,22,47,621,11,4400,3400,800,900,53,93,10.4,16,9268,92 322 | Lock Haven University of Pennsylvania,No,3570,2215,651,17,41,3390,325,7352,3620,225,500,47,55,16.1,14,6374,63 323 | Longwood College,No,2747,1870,724,12,47,2874,118,7920,3962,550,2200,74,80,18.4,23,5553,62 324 | Loras College,Yes,1641,1283,527,20,39,1663,170,11200,4000,500,1200,61,62,14.2,24,7578,70 325 | Louisiana College,Yes,2013,1053,212,33,61,912,158,5150,3036,500,1655,64,74,10.5,11,7547,59 326 | Louisiana State University at Baton Rouge,No,5996,4993,3079,29,57,16269,3757,5925,2980,600,2242,83,87,15.9,11,6741,37 327 | Louisiana Tech University,No,2397,2144,1525,22,45,6720,1822,3957,2325,618,1656,66,77,20,13,4546,45 328 | Loyola College,Yes,4076,3137,738,25,54,3010,184,12990,6300,600,900,86,88,14.7,27,9448,80 329 | Loyola Marymount University,Yes,3768,2662,753,42,64,3558,436,13592,5916,545,1328,84,88,14.2,10,11677,84 330 | Loyola University,Yes,1891,1698,719,24,80,2740,761,11100,5870,600,750,77,88,11.7,14,9456,53 331 | Loyola University Chicago,Yes,3579,2959,868,25,55,5244,3417,11500,5330,700,2000,94,95,6.2,15,13009,65 332 | Luther College,Yes,1549,1392,587,38,72,2269,85,13240,3560,600,400,73,85,13.8,38,8949,77 333 | Lycoming College,Yes,1286,1005,363,16,37,1363,74,13900,4300,500,900,75,81,14,32,8024,72 334 | Lynchburg College,Yes,1756,1500,366,3,21,1524,280,12450,5400,450,870,62,66,12.4,24,8832,70 335 | Lyndon State College,No,535,502,223,6,20,959,150,7320,4640,500,600,48,65,12.6,15,7114,51 336 | Macalester College,Yes,2939,1496,452,56,86,1723,113,15909,4772,500,700,85,91,11.9,37,14213,77 337 | MacMurray College,Yes,740,558,177,12,29,628,63,9620,3750,550,950,49,55,10.8,33,10642,59 338 | Malone College,Yes,874,758,428,21,46,1605,246,9858,3700,450,1200,42,45,17.6,16,4796,55 339 | Manchester College,Yes,1004,802,239,23,63,909,51,10440,3850,525,1450,63,72,11.8,20,7940,64 340 | Manhattan College,Yes,2432,1730,563,20,63,2578,254,12370,6800,500,1800,92,92,13.6,25,10062,79 341 | Manhattanville College,Yes,962,750,212,21,54,830,150,14700,6550,450,400,97,97,11.3,24,11291,70 342 | Mankato State University,No,3073,2672,1547,9,29,9649,1792,4300,2643,450,1660,57,68,19,11,5801,68 343 | Marian College of Fond du Lac,Yes,824,670,337,15,41,1160,653,9400,3400,500,1100,37,37,8.4,21,5352,59 344 | Marietta College,Yes,1611,960,342,27,60,1089,210,13850,3920,470,810,80,97,13.2,30,10223,96 345 | Marist College,Yes,4731,3171,830,12,31,3557,658,10700,5925,550,1200,74,81,17.6,34,8408,69 346 | Marquette University,Yes,5152,4600,1685,36,71,7016,804,11610,4760,600,1950,86,94,13.5,25,9982,77 347 | Marshall University,Yes,4226,3666,2007,14,60,7703,2339,5094,4010,700,1560,77,86,16.6,10,6203,50 348 | Mary Baldwin College,Yes,499,441,199,26,52,846,377,11200,7400,600,1300,66,79,6.8,50,10819,90 349 | Mary Washington College,No,4350,2178,756,39,78,2997,736,6490,4942,650,2102,75,80,17.6,30,5358,84 350 | Marymount College Tarrytown,Yes,478,327,117,9,34,731,370,11510,6450,575,1075,71,93,10.3,30,10502,77 351 | Marymount Manhattan College,Yes,695,535,239,21,30,988,785,10200,7000,350,1100,63,76,11.7,20,10622,68 352 | Marymount University,Yes,941,772,214,10,30,1247,776,11390,5280,500,750,77,82,10.6,17,8575,55 353 | Maryville College,Yes,1464,888,176,26,52,624,128,11200,4208,500,1642,80,90,11.1,43,8317,51 354 | Maryville University,Yes,549,397,169,26,51,1343,1751,9250,4550,425,1350,52,58,13.1,13,5925,61 355 | Marywood College,Yes,1107,859,323,13,51,1452,402,11040,4500,600,700,65,76,11.8,30,9034,66 356 | Massachusetts Institute of Technology,Yes,6411,2140,1078,96,99,4481,28,20100,5975,725,1600,99,99,10.1,35,33541,94 357 | Mayville State University,No,233,233,153,5,12,658,58,4486,2516,600,1900,68,68,15.7,11,6971,51 358 | McKendree College,Yes,1002,555,119,16,43,836,684,7680,3740,500,800,70,74,17.7,21,6652,52 359 | McMurry University,Yes,578,411,187,25,50,880,477,6930,3452,400,1525,57,64,11,11,6383,32 360 | McPherson College,Yes,420,293,93,11,32,336,80,7950,3750,600,2740,54,54,9.8,45,9754,48 361 | Mercer University,Yes,2286,1668,564,37,70,2943,1260,11985,4081,400,1500,93,95,9.2,15,8995,91 362 | Mercyhurst College,Yes,1557,1074,397,15,40,1805,433,9813,4050,425,1000,45,63,16.7,29,7307,78 363 | Meredith College,Yes,857,772,376,25,58,1721,470,6720,3250,450,1520,77,82,13.9,33,6881,82 364 | Merrimack College,Yes,1981,1541,514,18,36,1927,1084,12500,6200,375,1000,73,75,16.8,22,8707,80 365 | Mesa State College,No,1584,1456,891,6,18,3471,911,5016,3798,540,2256,48,48,28.8,12,3871,59 366 | Messiah College,Yes,1742,1382,607,30,64,2258,53,10300,5080,475,1200,68,75,14.1,30,7762,89 367 | Miami University at Oxford,No,9239,7788,3290,35,39,13606,807,8856,3960,500,1382,81,89,17.6,20,7846,85 368 | Michigan State University,No,18114,15096,6180,23,57,26640,4120,10658,3734,504,600,93,95,14,9,10520,71 369 | Michigan Technological University,No,2618,2288,1032,42,77,5524,414,8127,3978,900,1200,82,82,17,25,7473,65 370 | MidAmerica Nazarene College,Yes,331,331,225,15,36,1100,166,6840,3720,1100,4913,33,33,15.4,20,5524,49 371 | Millersville University of Penn.,No,6011,3075,960,22,60,5146,1532,7844,3830,450,1258,72,74,16.8,20,7832,71 372 | Milligan College,Yes,610,461,189,26,52,685,49,8200,3300,550,1000,63,69,12,16,8128,64 373 | Millikin University,Yes,1444,1261,456,29,62,1788,95,11910,4378,450,965,60,77,11.4,25,8149,75 374 | Millsaps College,Yes,905,834,319,32,61,1073,179,11320,4402,550,1350,82,89,12.7,38,11218,58 375 | Milwaukee School of Engineering,Yes,1217,1088,496,36,69,1773,884,11505,3255,1000,2075,35,46,16.7,23,7140,67 376 | Mississippi College,Yes,594,385,307,36,57,1695,721,5580,2830,600,700,77,79,16.5,18,6170,61 377 | Mississippi State University,No,4255,3277,1609,18,57,10094,1621,9866,3084,480,1479,77,77,15.9,20,6223,53 378 | Mississippi University for Women,No,480,405,380,19,46,1673,1014,4386,2217,600,1500,49,54,15.8,8,5704,63 379 | Missouri Southern State College,No,1576,1326,913,13,50,3689,2200,3840,2852,200,400,52,54,20.3,9,4172,100 380 | Missouri Valley College,Yes,1310,983,316,5,35,1057,175,8550,5050,400,900,35,67,17.4,16,4333,27 381 | Monmouth College IL,Yes,601,503,204,28,57,671,11,13000,4100,400,460,91,91,11.6,43,11087,56 382 | Monmouth College,Yes,2707,1881,478,14,34,1893,847,12480,5290,530,1740,70,85,14.2,15,9492,54 383 | Montana College of Mineral Sci. & Tech.,No,572,544,320,45,72,1470,416,6073,3400,550,1400,71,71,16.4,31,6112,74 384 | Montana State University,No,3500,2836,1779,15,42,8730,993,5552,3710,550,2300,75,83,17.6,8,6324,37 385 | Montclair State University,No,5220,2128,865,19,53,6411,3186,3648,4834,700,950,82,87,21.5,9,6717,58 386 | Montreat-Anderson College,Yes,263,223,103,10,24,316,20,8438,3372,500,2958,42,50,11.1,4,11989,15 387 | Moorhead State University,No,2442,2164,1189,12,37,5983,1075,4426,2664,600,1000,76,81,18.1,19,4795,60 388 | Moravian College,Yes,1232,955,303,23,58,1241,485,14990,4730,550,1250,86,92,15.2,28,9566,74 389 | Morehouse College,Yes,3708,1678,722,41,66,2852,153,7050,5490,250,600,71,74,17.8,10,8122,83 390 | Morningside College,Yes,586,533,239,16,36,950,228,10520,3678,500,1000,48,68,13,32,8111,56 391 | Morris College,Yes,882,730,330,2,13,926,12,4515,2550,850,2100,53,60,18.6,34,6990,60 392 | Mount Holyoke College,Yes,1800,1314,526,47,79,1891,40,19300,5700,750,750,79,91,9,51,18359,84 393 | Mount Marty College,Yes,279,276,126,17,37,600,435,6844,2980,500,500,45,55,11.7,38,5073,44 394 | Mount Mary College,Yes,235,217,121,12,32,931,487,8950,3119,550,1125,51,51,10.7,26,7016,78 395 | Mount Mercy College,Yes,368,317,159,20,49,806,542,10500,3555,500,2285,44,50,11.3,30,6695,64 396 | Mount Saint Clare College,Yes,325,284,95,16,33,364,88,9900,3650,500,1200,32,37,13.6,43,6525,21 397 | Mount Saint Mary's College,Yes,1321,1159,328,15,36,1243,79,12850,6200,550,900,77,82,12.8,36,8536,80 398 | Mount Saint Mary College,Yes,1170,695,238,14,48,1170,429,7470,4600,250,1400,74,75,15.3,23,6898,88 399 | Mount St. Mary's College,Yes,657,537,113,37,90,1039,466,12474,5678,630,1278,53,71,11.9,19,10613,72 400 | Mount Union College,Yes,1310,1086,458,26,61,1365,144,12250,3530,400,1150,85,87,16.7,35,7215,81 401 | Mount Vernon Nazarene College,Yes,510,485,334,18,36,1114,94,7400,3346,600,600,57,57,19.8,7,6869,58 402 | Muhlenberg College,Yes,2519,1836,462,30,61,1656,352,16975,4565,600,850,76,86,12.8,39,10888,83 403 | Murray State University,No,2225,1910,1190,29,55,5968,955,4738,3110,700,940,72,76,20.2,27,5972,52 404 | Muskingum College,Yes,1109,922,375,24,46,1115,70,13240,3914,600,800,73,85,13.4,27,9333,73 405 | National-Louis University,Yes,513,347,279,23,48,2508,505,9090,4500,650,500,62,65,18.3,2,7905,71 406 | Nazareth College of Rochester,Yes,947,798,266,36,68,1274,471,10850,5150,550,800,77,93,13.6,24,8797,61 407 | New Jersey Institute of Technology,No,1879,1216,483,27,62,3311,1646,8832,5376,700,1850,92,98,13.5,19,12529,72 408 | New Mexico Institute of Mining and Tech.,No,787,601,233,40,73,1017,411,5376,3214,600,1100,99,100,13.7,11,9241,34 409 | New York University,Yes,13594,7244,2505,70,86,12408,2814,17748,7262,450,1000,87,98,7.8,16,21227,71 410 | Newberry College,Yes,872,722,154,14,36,601,36,10194,2600,500,1500,57,63,11.4,32,5788,83 411 | Niagara University,Yes,2220,1796,467,65,99,1919,334,10320,4762,450,650,68,100,14.2,20,7788,65 412 | North Adams State College,No,1563,1005,240,1,19,1380,136,5542,4330,500,1000,65,71,14.2,17,6562,57 413 | North Carolina A. & T. State University,No,4809,3089,1429,12,33,6162,871,6806,1780,600,1651,72,72,16.7,9,7090,44 414 | North Carolina State University at Raleigh,No,10634,7064,3176,39,78,16505,5481,8400,6540,600,1300,92,98,17.5,21,9670,62 415 | North Carolina Wesleyan College,Yes,812,689,195,7,24,646,84,8242,4230,600,1295,77,77,12.7,11,10090,52 416 | North Central College,Yes,1127,884,308,30,64,1310,766,11718,7398,450,1800,73,87,16.4,33,8871,76 417 | North Dakota State University,No,2968,2297,1610,13,47,7368,1128,5834,2744,600,2000,79,83,17,24,6310,42 418 | North Park College,Yes,465,361,176,19,39,879,156,12580,4345,400,970,76,79,13.1,24,10889,74 419 | Northeast Missouri State University,No,6040,4577,1620,36,72,5640,266,4856,3416,400,1100,69,72,15.7,13,6601,76 420 | Northeastern University,Yes,11901,8492,2517,16,42,11160,10221,13380,7425,600,1750,73,82,12.9,17,9563,46 421 | Northern Arizona University,No,5891,4931,1973,23,48,11249,2682,6746,3728,620,2342,78,83,21.7,7,6157,41 422 | Northern Illinois University,No,10706,7219,2397,12,37,14826,1979,7799,3296,470,1750,73,78,17.3,11,6086,56 423 | Northwest Missouri State University,No,2729,2535,1257,8,29,4787,472,3735,3136,250,1630,62,65,21.7,23,5284,54 424 | Northwest Nazarene College,Yes,616,514,385,29,52,1115,60,9840,2820,450,822,59,59,14.8,20,6261,58 425 | Northwestern College,Yes,860,811,366,22,56,1040,52,9900,3075,300,1800,68,68,14.9,34,6357,68 426 | Northwestern University,Yes,12289,5200,1902,85,98,7450,45,16404,5520,759,1585,96,100,6.8,25,26385,92 427 | Norwich University,Yes,1743,1625,626,8,29,1862,382,14134,5270,500,800,71,74,13.1,22,9209,63 428 | Notre Dame College,Yes,379,324,107,15,37,500,311,9990,4900,400,600,44,47,12.1,26,4948,33 429 | Oakland University,No,3041,2581,1173,16,56,6441,3982,9114,4030,400,650,88,90,19.7,13,6637,53 430 | Oberlin College,Yes,4778,2767,678,50,89,2587,120,19670,5820,575,1119,77,96,10.1,47,16593,83 431 | Occidental College,Yes,2324,1319,370,52,81,1686,35,16560,5140,558,1152,91,93,10.5,30,16196,79 432 | Oglethorpe University,Yes,792,649,186,56,87,769,377,12900,4340,600,4110,91,95,13.1,27,8568,67 433 | Ohio Northern University,Yes,2936,2342,669,35,62,2502,66,15990,4080,600,825,73,78,14.5,31,9979,83 434 | Ohio University,No,11023,8298,3183,21,54,14861,1310,7629,4095,550,2300,79,87,20.4,13,8811,64 435 | Ohio Wesleyan University,Yes,2190,1700,458,36,65,1780,48,16732,5650,550,550,93,93,12.1,32,12011,75 436 | Oklahoma Baptist University,Yes,758,681,484,35,59,1707,705,5390,3140,515,1290,63,71,15.1,18,5511,50 437 | Oklahoma Christian University,Yes,776,765,351,22,44,1419,228,6400,3150,500,1900,58,64,16.2,8,6578,45 438 | Oklahoma State University,No,4522,3913,2181,29,57,12830,1658,5336,3344,800,3100,84,92,15.3,14,6433,48 439 | Otterbein College,Yes,1496,1205,428,26,57,1648,936,12888,4440,420,840,62,68,13.9,30,8802,87 440 | Ouachita Baptist University,Yes,910,773,450,31,73,1310,61,6530,2800,500,1500,63,67,13.3,10,6413,65 441 | Our Lady of the Lake University,Yes,2308,1336,295,22,46,1202,942,8530,3644,616,1576,56,64,14.9,25,7114,37 442 | Pace University,Yes,8256,3750,1522,37,70,5809,4379,11000,5160,660,1115,90,95,13.8,10,10059,62 443 | Pacific Lutheran University,Yes,1603,1392,504,31,68,2580,302,13312,4488,600,1516,78,78,11,23,9431,83 444 | Pacific Union College,Yes,940,668,385,20,48,1316,139,11925,3825,630,1926,48,87,12.3,12,9157,69 445 | Pacific University,Yes,943,849,288,41,71,1041,35,14210,3994,450,1100,76,76,10.9,22,11216,42 446 | Pembroke State University,No,944,774,440,14,34,2174,529,6360,2760,550,1498,77,77,15,5,6443,48 447 | Pennsylvania State Univ. Main Campus,No,19315,10344,3450,48,93,28938,2025,10645,4060,512,2394,77,96,18.1,19,8992,63 448 | Pepperdine University,Yes,3821,2037,680,86,96,2488,625,18200,6770,500,700,95,98,11.6,13,16185,66 449 | Peru State College,No,701,501,458,10,40,959,457,2580,2624,500,900,48,100,20.1,24,4870,44 450 | Pfeiffer College,Yes,838,651,159,11,25,654,162,8640,3700,400,1915,62,62,12.2,13,7634,48 451 | Philadelphia Coll. of Textiles and Sci.,Yes,1538,1259,468,19,42,1664,1042,11690,5062,600,1664,48,80,12.9,15,8028,68 452 | Phillips University,Yes,692,576,174,19,50,597,83,10500,3860,600,940,58,64,11.6,19,8990,39 453 | Piedmont College,Yes,663,562,127,20,40,641,63,5640,3620,600,750,89,89,13.2,17,7309,31 454 | Pikeville College,Yes,404,400,169,28,48,797,100,6000,3000,500,500,48,57,13.4,14,5557,61 455 | Pitzer College,Yes,1133,630,220,37,73,750,30,17688,5900,650,850,100,100,10.4,11,14820,73 456 | Point Loma Nazarene College,Yes,809,687,428,20,43,1889,217,10178,4190,800,750,71,71,16.1,19,7895,54 457 | Point Park College,Yes,875,744,207,7,38,1173,1402,9700,4830,400,1200,45,90,14.5,10,7652,66 458 | Polytechnic University,Yes,1132,847,302,58,89,1379,214,16200,4200,436,2486,90,90,10.4,14,14329,62 459 | Prairie View A. and M. University,No,2405,2234,1061,10,22,4564,448,4290,3500,598,1582,55,93,19.4,1,5967,35 460 | Presbyterian College,Yes,1082,832,302,34,63,1133,30,11859,3635,554,1429,80,85,13.4,42,8354,85 461 | Princeton University,Yes,13218,2042,1153,90,98,4540,146,19900,5910,675,1575,91,96,8.4,54,28320,99 462 | Providence College,Yes,5139,3346,973,20,55,3717,1358,14400,6200,450,1100,66,74,18.4,35,8135,96 463 | Purdue University at West Lafayette,No,21804,18744,5874,29,60,26213,4065,9556,3990,570,1060,86,86,18.2,15,8604,67 464 | Queens College,Yes,516,392,154,32,62,630,549,11020,4970,610,1900,73,75,14,36,9315,58 465 | Quincy University,Yes,1025,707,297,22,66,1070,72,10100,4140,450,1080,69,71,16.3,32,6880,80 466 | Quinnipiac College,Yes,3712,2153,806,17,45,2677,714,12030,6140,1000,500,63,73,12,33,8847,86 467 | Radford University,No,5702,4894,1742,15,37,8077,472,6684,4110,500,900,73,83,19.6,9,4519,62 468 | Ramapo College of New Jersey,No,2088,957,362,6,29,2745,1938,4449,4860,600,1655,74,95,17.8,8,7333,47 469 | Randolph-Macon College,Yes,1771,1325,306,21,46,1071,27,13840,3735,400,900,77,80,10.7,38,11080,74 470 | Randolph-Macon Woman's College,Yes,696,616,169,35,66,653,56,13970,6110,370,920,88,97,9.2,24,16358,68 471 | Reed College,Yes,1966,1436,327,47,80,1199,61,19960,5490,500,450,90,90,11.8,37,15886,68 472 | Regis College,Yes,427,385,143,18,38,581,533,12700,5800,450,700,81,85,10.3,37,11758,84 473 | Rensselaer Polytechnic Institute,Yes,4996,4165,936,53,82,4291,16,17475,5976,1230,1100,94,98,15.4,21,15605,70 474 | Rhodes College,Yes,2302,1831,391,58,82,1345,59,15200,4768,550,1500,90,96,10.8,47,13388,77 475 | Rider University,Yes,3586,2424,730,16,31,2748,1309,13250,5420,700,3100,84,92,12.3,23,11299,70 476 | Ripon College,Yes,587,501,211,28,52,735,28,15200,4100,350,650,87,90,9.4,49,12472,64 477 | Rivier College,Yes,484,386,141,6,28,590,1196,9870,4860,600,1100,59,59,12.2,19,6744,81 478 | Roanoke College,Yes,2227,1790,437,27,54,1460,239,13425,4425,450,1200,85,89,13,26,9405,72 479 | Rockhurst College,Yes,935,858,345,22,50,1127,754,9490,4100,500,1500,60,79,10.7,21,7519,79 480 | Rocky Mountain College,Yes,560,392,270,11,31,743,118,8734,3362,600,625,56,78,11.3,27,6422,68 481 | Roger Williams University,Yes,3304,2804,679,10,20,2111,1489,12520,6050,500,730,44,54,16.4,8,7957,61 482 | Rollins College,Yes,1777,1151,382,31,55,1668,1052,16425,5220,955,750,81,85,13.3,23,11561,90 483 | Rosary College,Yes,434,321,141,28,53,624,269,10950,4600,550,950,79,82,12.9,30,9264,81 484 | Rowan College of New Jersey,No,3820,1431,695,21,70,5303,3942,4356,4830,800,800,76,81,22.1,6,7252,51 485 | Rutgers at New Brunswick,No,48094,26330,4520,36,79,21401,3712,7410,4748,690,2009,90,95,19.5,19,10474,77 486 | Rutgers State University at Camden,No,3366,1752,232,27,79,2585,1300,7411,4748,690,2009,90,95,18.6,12,10134,57 487 | Rutgers State University at Newark,No,5785,2690,499,26,62,4005,1886,7410,4748,690,2009,90,95,17.4,16,11878,58 488 | Sacred Heart University,Yes,2307,1896,509,19,51,1707,1889,11070,5780,400,600,71,73,14.8,16,7120,82 489 | Saint Ambrose University,Yes,897,718,276,12,48,1345,390,10450,4020,500,1500,56,56,14.1,16,7444,70 490 | Saint Anselm College,Yes,2095,1553,514,15,40,1873,94,12950,5400,450,1120,70,82,14.5,29,6719,97 491 | Saint Cloud State University,No,3971,3306,1921,10,34,11493,2206,4259,2625,350,1884,70,75,18.9,10,4629,58 492 | Saint Francis College IN,Yes,213,166,85,13,36,513,247,8670,3820,450,1000,43,78,12.5,4,7440,48 493 | Saint Francis College,Yes,1046,824,284,21,45,1223,451,10880,5050,400,1235,64,64,19.3,24,7344,69 494 | Saint John's University,Yes,933,800,444,18,45,1691,72,12247,4081,500,600,76,85,12,38,9853,70 495 | Saint Joseph's College IN,Yes,920,684,225,24,42,815,222,11200,4250,600,950,55,60,14.8,19,7360,67 496 | Saint Joseph's College,Yes,833,682,217,12,33,716,2196,9985,5180,500,800,53,89,27.2,8,4322,85 497 | Saint Joseph's University,Yes,2519,2003,776,39,71,2473,1314,12750,6350,350,1690,84,90,17.4,13,8243,83 498 | Saint Joseph College,Yes,292,241,96,20,52,543,712,12200,4600,650,950,87,90,11.2,32,8680,76 499 | Saint Louis University,Yes,3294,2855,956,44,67,4576,1140,11690,4730,800,6800,84,94,4.6,19,18367,67 500 | Saint Mary's College,Yes,888,734,393,26,60,1433,27,12730,4514,500,1525,74,95,9.9,31,11165,98 501 | Saint Mary's College of Minnesota,Yes,876,802,367,14,35,1263,118,10800,3600,400,820,68,74,18.8,19,5081,78 502 | Saint Mary-of-the-Woods College,Yes,150,130,88,23,50,341,768,10300,4130,500,1700,44,58,10.2,37,9678,75 503 | Saint Michael's College,Yes,1910,1380,463,16,64,1715,106,13030,5860,500,750,79,88,14.5,34,10190,84 504 | Saint Olaf College,Yes,2248,1673,745,38,73,2888,105,14350,3750,550,550,82,88,10,31,12502,83 505 | Saint Peter's College,Yes,1606,1413,530,23,38,1921,1154,9408,5520,500,450,78,78,12.1,22,7669,53 506 | Saint Vincent College,Yes,700,595,278,19,35,1035,182,10850,3936,500,900,62,64,12.3,31,8534,88 507 | Saint Xavier University,Yes,785,647,295,15,65,1670,726,10860,4624,600,794,87,100,13.7,15,8953,55 508 | Salem-Teikyo University,Yes,489,384,120,23,52,700,45,10575,3952,400,620,46,24,13,9,8946,98 509 | Salem College,Yes,335,284,132,28,69,534,216,10475,6300,500,2000,68,68,11.2,46,9599,60 510 | Salisbury State University,No,4216,2290,736,20,52,4296,1027,5130,4690,600,1450,73,75,17.9,18,5125,56 511 | Samford University,Yes,1680,1395,691,34,76,2959,402,8236,3700,569,1650,74,75,14.7,17,9533,61 512 | San Diego State University,No,9402,7020,2151,20,70,16407,5550,8384,5110,612,2400,87,93,19.5,7,7930,41 513 | Santa Clara University,Yes,4019,2779,888,40,73,3891,128,13584,5928,630,1278,88,92,13.9,19,10872,100 514 | Sarah Lawrence College,Yes,1380,768,263,57,82,1000,105,19300,6694,600,700,89,93,6.1,18,14779,83 515 | Savannah Coll. of Art and Design,Yes,1109,688,386,20,65,1897,208,8325,5000,1200,1600,14,98,16.1,26,6874,55 516 | Schreiner College,Yes,584,413,131,19,51,521,99,8955,5900,500,1488,51,56,11.8,23,8545,52 517 | Scripps College,Yes,855,632,139,60,83,569,7,17238,7350,600,800,95,100,8.2,41,18372,73 518 | Seattle Pacific University,Yes,1183,1016,411,42,82,1922,704,12669,4875,600,1250,83,85,16.8,20,10368,66 519 | Seattle University,Yes,2115,1540,494,28,72,2993,347,12825,4375,500,1500,85,85,12.2,16,10175,89 520 | Seton Hall University,Yes,4576,3565,1000,16,36,4384,1530,12000,6484,650,1000,81,84,14.4,15,10080,64 521 | Seton Hill College,Yes,936,794,197,24,56,752,210,11240,4180,350,2000,71,71,11.2,37,10065,71 522 | Shippensburg University of Penn.,No,5818,3281,1116,14,53,5268,300,7844,3504,450,1700,80,83,18.8,13,6719,72 523 | Shorter College,Yes,540,445,165,23,70,1115,111,7210,3600,500,2000,62,65,13.2,18,7356,58 524 | Siena College,Yes,2961,1932,628,24,68,2669,616,10800,5100,575,1090,71,82,14.1,42,8189,100 525 | Siena Heights College,Yes,464,419,183,10,31,686,287,9240,3880,475,1090,29,49,7.2,17,9431,47 526 | Simmons College,Yes,1003,782,295,23,53,1144,160,16160,6950,500,1200,74,81,8.9,33,14086,79 527 | Simpson College,Yes,1016,872,300,27,57,1116,602,11250,4980,550,1400,66,73,15.8,36,7411,70 528 | Sioux Falls College,Yes,437,400,211,13,35,614,271,8990,3064,500,1700,73,73,14.8,7,7881,48 529 | Skidmore College,Yes,4293,2728,591,25,62,2322,263,18710,5970,500,700,87,92,12.7,29,14837,81 530 | Smith College,Yes,2925,1598,632,51,88,2479,95,18820,6390,500,1050,85,97,10.3,44,21199,90 531 | South Dakota State University,No,2807,2589,1701,13,37,7000,1103,3811,2190,500,1970,62,65,15,29,5084,67 532 | Southeast Missouri State University,No,2281,1870,1408,18,43,6553,1246,4680,3540,200,2150,75,76,17.1,8,5916,45 533 | Southeastern Oklahoma State Univ.,No,818,700,447,20,50,2962,651,3738,2619,450,1022,55,59,19.6,9,4444,53 534 | Southern California College,Yes,385,340,193,18,38,784,127,9520,4124,630,1818,63,65,18.6,11,8219,43 535 | Southern Illinois University at Edwardsville,No,2540,2195,994,13,40,6063,2550,5472,3598,221,2216,76,81,16.5,8,7498,43 536 | Southern Methodist University,Yes,4301,3455,1166,41,69,4892,387,12772,5078,576,1802,74,88,13.5,17,12726,72 537 | Southwest Baptist University,Yes,1093,1093,642,12,32,1770,967,7070,2500,400,1000,52,54,15.9,13,4718,71 538 | Southwest Missouri State University,No,6118,5254,3204,15,37,13131,3374,4740,2590,500,1360,70,75,19.9,11,4632,56 539 | Southwest State University,No,1047,938,511,13,33,2091,546,4285,2750,600,1800,58,75,16.5,31,6591,51 540 | Southwestern Adventist College,Yes,321,318,172,11,27,620,280,7536,3736,430,1651,44,77,13,12,5309,36 541 | Southwestern College,Yes,213,155,75,28,66,504,147,7200,3532,550,1500,56,56,11.8,12,7818,52 542 | Southwestern University,Yes,1244,912,352,44,77,1177,43,11850,4675,600,1050,83,89,11.3,35,12995,67 543 | Spalding University,Yes,283,201,97,10,45,589,263,8400,2800,600,900,50,56,10.6,40,6860,89 544 | Spelman College,Yes,3713,1237,443,47,83,1971,107,7000,5565,660,2400,73,80,12.5,18,9988,65 545 | Spring Arbor College,Yes,372,362,181,15,32,1501,353,8600,3550,385,665,48,48,15.4,9,10938,49 546 | St. Bonaventure University,Yes,1489,1313,375,13,45,1688,131,10456,4927,500,1050,91,91,17.7,32,9828,78 547 | St. John's College,Yes,323,278,122,31,51,393,4,16150,5450,275,800,63,72,7.2,26,15622,64 548 | St. John Fisher College,Yes,1368,1064,354,19,51,1687,677,10570,5600,400,800,86,81,14.5,29,7908,66 549 | St. Lawrence University,Yes,2753,1820,505,31,56,1801,45,18720,5730,650,825,90,94,11.5,38,14980,85 550 | St. Martin's College,Yes,191,165,63,5,25,494,574,11550,4270,300,500,43,77,14.5,8,9209,40 551 | St. Mary's College of California,Yes,2643,1611,465,36,80,2615,248,13332,6354,630,1584,88,89,16.1,17,9619,78 552 | St. Mary's College of Maryland,No,1340,695,285,42,73,1315,209,6800,4730,675,1250,84,89,11.6,23,10357,63 553 | St. Mary's University of San Antonio,Yes,1243,1020,414,33,60,2149,418,8678,3858,700,1736,82,83,16.2,7,7651,72 554 | St. Norbert College,Yes,1334,1243,568,30,56,1946,95,12140,4450,425,1100,74,78,15.1,36,8595,88 555 | St. Paul's College,Yes,651,581,243,8,17,617,34,5000,3650,600,600,45,45,14,8,8426,45 556 | St. Thomas Aquinas College,Yes,861,609,215,10,27,1117,815,8650,5700,500,1750,69,73,16.1,13,6534,67 557 | Stephens College,Yes,450,405,194,17,34,614,388,13900,5200,450,2150,46,63,10.9,17,9995,59 558 | Stetson University,Yes,1557,1227,489,37,69,1964,81,12315,4565,600,1365,85,90,12.5,24,10307,73 559 | Stevens Institute of Technology,Yes,1768,1249,380,51,93,1263,11,16900,5680,450,750,89,89,19,33,12837,79 560 | Stockton College of New Jersey,No,4019,1579,710,23,65,4365,765,3040,4351,711,1125,78,92,19.5,7,5599,64 561 | Stonehill College,Yes,3646,2300,585,25,69,2022,926,12170,6172,480,800,79,79,13,30,7495,97 562 | SUNY at Albany,No,13528,9198,1843,16,61,10168,1231,6550,4355,700,1560,93,96,17.4,16,9075,74 563 | SUNY at Binghamton,No,14463,6166,1757,60,94,8544,671,6550,4598,700,1000,83,100,18,15,8055,80 564 | SUNY at Buffalo,No,15039,9649,3087,36,100,13963,3124,6550,4731,708,957,90,97,13.6,15,11177,56 565 | SUNY at Stony Brook,No,12512,6969,1724,27,66,9744,1351,6550,4712,600,1200,91,96,10.5,7,13705,57 566 | SUNY College at Brockport,No,7294,3564,904,7,34,5758,1363,6550,4460,500,705,79,83,19,14,6632,49 567 | SUNY College at Oswego,No,8000,4556,1464,17,70,6943,869,6550,4810,500,1500,69,85,22,21,5280,63 568 | SUNY College at Buffalo,No,5318,3515,1025,8,29,7626,2091,6550,4040,550,1230,71,78,18.7,12,7511,42 569 | SUNY College at Cortland,No,7888,3519,1036,6,40,5011,346,6550,4680,630,1274,82,85,17.8,17,5563,53 570 | SUNY College at Fredonia,No,4877,2798,814,13,48,4123,298,6550,4420,620,1481,82,90,16.3,10,6442,66 571 | SUNY College at Geneseo,No,8598,4562,1143,56,93,5060,146,6550,4170,600,650,79,84,19.1,25,5716,76 572 | SUNY College at New Paltz,No,8399,3609,656,19,53,4658,1478,6550,4240,550,1500,85,93,15.3,8,6608,53 573 | SUNY College at Plattsburgh,No,5549,3583,853,9,40,5004,475,6550,4176,600,1380,80,90,17.9,16,6174,65 574 | SUNY College at Potsdam,No,3150,2289,650,16,51,3598,234,6840,4660,500,1000,71,75,15.1,17,6436,59 575 | SUNY College at Purchase,No,2119,1264,390,5,33,2478,1441,6550,4760,1125,1362,80,100,14.9,8,8170,46 576 | Susquehanna University,Yes,2096,1512,465,27,59,1442,166,16130,4710,400,800,83,86,13.9,37,10554,90 577 | Sweet Briar College,Yes,462,402,146,36,68,527,41,14500,6000,500,600,91,99,6.5,48,18953,61 578 | Syracuse University,Yes,10477,7260,2442,28,67,10142,117,15150,6870,635,960,73,84,11.3,13,14231,67 579 | Tabor College,Yes,257,183,109,19,41,396,38,7850,3410,400,1500,55,70,10,15,7233,53 580 | Talladega College,Yes,4414,1500,335,30,60,908,119,5666,2964,1000,1400,56,58,15.5,7,5970,46 581 | Taylor University,Yes,1769,1092,437,41,80,1757,81,10965,4000,450,1250,60,61,14.2,32,8294,98 582 | Tennessee Wesleyan College,Yes,232,182,99,7,29,402,237,7070,3640,400,3158,59,65,8.9,16,6286,36 583 | Texas A&M Univ. at College Station,No,14474,10519,6392,49,85,31643,2798,5130,3412,600,2144,89,91,23.1,29,8471,69 584 | Texas A&M University at Galveston,No,529,481,243,22,47,1206,134,4860,3122,600,650,103,88,17.4,16,6415,43 585 | Texas Christian University,Yes,4095,3079,1195,33,64,5064,660,8490,3320,650,2400,81,93,14.8,23,9158,64 586 | Texas Lutheran College,Yes,497,423,215,27,57,895,429,7850,3410,490,1700,54,58,13.8,24,7002,50 587 | Texas Southern University,No,4345,3245,2604,15,85,5584,3101,7860,3360,600,1700,65,75,18.2,21,3605,10 588 | Texas Wesleyan University,Yes,592,501,279,19,44,1204,392,6400,3484,600,1800,80,83,14.5,10,7936,43 589 | The Citadel,No,1500,1242,611,12,36,2024,292,7070,2439,400,779,95,94,17.1,17,7744,84 590 | Thiel College,Yes,1154,951,253,15,31,791,140,11172,4958,700,1350,68,76,11.6,16,9186,60 591 | Tiffin University,Yes,845,734,254,5,21,662,351,7600,3800,600,1200,59,74,19,40,5096,39 592 | Transylvania University,Yes,759,729,244,57,81,867,51,10900,4450,500,1000,81,91,12.1,41,10219,70 593 | Trenton State College,No,5042,2312,944,55,94,5167,902,5391,5411,700,1000,81,87,14.4,6,8504,81 594 | Tri-State University,Yes,1262,1102,276,14,40,978,98,9456,4350,468,1323,53,53,12.8,24,7603,65 595 | Trinity College CT,Yes,3058,1798,478,46,84,1737,244,18810,5690,500,680,91,96,10.4,48,18034,91 596 | Trinity College DC,Yes,247,189,100,19,49,309,639,11412,6430,500,900,89,93,8.3,37,11806,96 597 | Trinity College VT,Yes,222,185,91,16,41,484,541,11010,5208,550,500,58,78,10.4,26,9586,78 598 | Trinity University,Yes,2425,1818,601,62,93,2110,95,12240,5150,500,490,94,96,9.6,20,14703,93 599 | Tulane University,Yes,7033,5125,1223,47,75,4941,1534,19040,5950,350,800,98,98,9.1,21,16920,74 600 | Tusculum College,Yes,626,372,145,12,34,983,40,7700,3400,450,800,70,70,21.9,28,4933,52 601 | Tuskegee University,Yes,2267,1827,611,20,59,2825,144,6735,3395,600,1425,70,74,12.2,7,10872,65 602 | Union College KY,Yes,484,384,177,9,45,634,78,7800,2950,500,600,60,88,14.1,9,6864,64 603 | Union College NY,Yes,3495,1712,528,49,84,1915,123,18732,6204,450,1024,94,96,11.5,49,15411,88 604 | Univ. of Wisconsin at OshKosh,No,4800,2900,1515,14,48,7764,1472,6874,2394,518,1890,73,78,19.2,14,5901,56 605 | University of Alabama at Birmingham,No,1797,1260,938,24,35,6960,4698,4440,5175,750,2200,96,96,6.7,16,16352,33 606 | University of Arkansas at Fayetteville,No,3235,3108,2133,25,65,9978,1530,5028,3300,500,2000,73,89,14.8,10,6820,39 607 | University of California at Berkeley,No,19873,8252,3215,95,100,19532,2061,11648,6246,636,1933,93,97,15.8,10,13919,78 608 | University of California at Irvine,No,15698,10775,2478,85,100,12677,864,12024,5302,790,1818,96,96,16.1,11,15934,66 609 | University of Central Florida,No,6986,2959,1918,25,60,12330,7152,6618,4234,700,1600,80,98,22.2,9,6742,46 610 | University of Charleston,Yes,682,535,204,22,43,771,611,9500,3540,400,750,26,58,2.5,10,7683,57 611 | University of Chicago,Yes,6348,2999,922,68,94,3340,39,18930,6380,500,1254,99,99,5.3,36,36854,90 612 | University of Cincinnati,No,6855,5553,2408,26,57,11036,2011,8907,4697,556,1851,89,95,10.8,6,13889,54 613 | University of Connecticut at Storrs,No,9735,7187,2064,23,63,12478,1660,11656,5072,700,2300,89,95,16,16,10178,71 614 | University of Dallas,Yes,681,588,246,44,74,1058,73,10760,6230,500,1200,85,93,13.4,26,8731,63 615 | University of Dayton,Yes,6361,5293,1507,26,51,5889,665,11380,4220,500,900,81,85,14.8,25,8894,93 616 | University of Delaware,Yes,14446,10516,3252,22,57,14130,4522,10220,4230,530,1300,82,87,18.3,15,10650,75 617 | University of Denver,Yes,2974,2001,580,29,60,2666,554,15192,4695,400,1350,84,91,15.9,21,11762,67 618 | University of Detroit Mercy,Yes,927,731,415,24,50,2149,2217,11130,3996,600,2166,72,79,13.5,14,10891,51 619 | University of Dubuque,Yes,576,558,137,11,39,662,131,10430,3620,400,1500,85,98,16.5,18,8767,45 620 | University of Evansville,Yes,2096,1626,694,35,67,2551,407,11800,4340,700,960,60,81,15.8,26,7780,77 621 | University of Florida,No,12445,8836,3623,54,85,24470,3286,7090,4180,630,1530,88,97,13.4,20,14737,66 622 | University of Georgia,No,11220,7871,3320,43,79,19553,2748,5697,3600,525,1755,88,95,14.7,22,7881,63 623 | University of Hartford,Yes,5081,4040,1194,11,26,3768,1415,14220,6000,500,1440,61,76,10.7,9,10625,66 624 | University of Hawaii at Manoa,No,3580,2603,1627,36,69,11028,2411,4460,3038,687,1281,85,87,11.8,6,12833,54 625 | University of Illinois - Urbana,No,14939,11652,5705,52,88,25422,911,7560,4574,500,1982,87,90,17.4,13,8559,81 626 | University of Illinois at Chicago,No,8384,5727,2710,22,50,13518,2916,7230,5088,630,3228,82,84,10,6,13883,34 627 | University of Indianapolis,Yes,1487,1276,388,26,51,1417,1646,11120,4080,525,1405,55,56,11.1,23,6735,69 628 | University of Kansas,No,8579,5561,3681,25,50,17880,1673,6994,3384,700,2681,88,94,13.7,17,9657,57 629 | University of La Verne,Yes,1597,969,226,16,38,1431,1522,13540,5050,630,2298,66,68,14.1,23,10139,47 630 | University of Louisville,No,4777,3057,1823,16,33,9844,6198,6540,3600,530,2440,84,92,11.1,24,10207,31 631 | University of Maine at Farmington,No,1208,803,438,20,48,1906,344,6810,3970,450,1647,67,75,15.9,26,5712,59 632 | University of Maine at Machias,No,441,369,172,17,45,633,317,6600,3680,600,400,46,46,15.1,4,5935,64 633 | University of Maine at Presque Isle,No,461,381,235,10,40,974,503,6600,3630,400,1675,67,67,15.2,11,6408,35 634 | University of Maryland at Baltimore County,No,4269,2594,985,27,57,6476,2592,8594,4408,494,2768,82,88,18.4,6,7618,55 635 | University of Maryland at College Park,No,14292,10315,3409,22,53,19340,3991,8723,5146,550,1550,89,92,18.1,12,9021,63 636 | University of Massachusetts at Amherst,No,14438,12414,3816,12,39,16282,1940,8566,3897,500,1400,88,92,16.7,15,10276,68 637 | University of Massachusetts at Dartmouth,No,3347,2597,1006,10,37,4664,1630,6919,4500,500,1250,74,90,15,20,7462,56 638 | University of Miami,Yes,7122,5386,1643,42,69,7760,876,16500,6526,630,1985,82,94,5.9,17,17500,59 639 | University of Michigan at Ann Arbor,No,19152,12940,4893,66,92,22045,1339,15732,4659,476,1600,90,98,11.5,26,14847,87 640 | University of Minnesota at Duluth,No,4192,3126,1656,15,45,5887,1254,8828,3474,753,2610,79,91,19,11,6393,53 641 | University of Minnesota at Morris,No,1458,874,588,56,86,1846,154,9843,3180,600,1500,74,78,14.6,16,6716,51 642 | University of Minnesota Twin Cities,No,11054,6397,3524,26,55,16502,21836,8949,3744,714,2910,88,90,12.2,37,16122,45 643 | University of Mississippi,No,3844,3383,1669,26,47,7524,804,4916,3810,600,550,81,86,20.3,14,6971,53 644 | University of Missouri at Columbia,No,6574,4637,2940,32,62,14782,1583,9057,3485,600,1983,87,87,12.7,15,10145,58 645 | University of Missouri at Rolla,No,1877,1826,823,49,77,3926,561,9057,3600,700,1435,88,88,14.4,23,9699,49 646 | University of Missouri at Saint Louis,No,1618,1141,479,18,54,4793,4552,7246,3964,500,4288,71,73,13.4,15,6433,48 647 | University of Mobile,Yes,452,331,269,17,54,1417,301,6150,3680,550,1200,59,63,16.6,4,5412,52 648 | University of Montevallo,No,1351,892,570,18,78,2385,331,4440,3030,300,600,72,72,18.9,8,5883,51 649 | University of Nebraska at Lincoln,No,6277,6003,3526,33,63,16454,3171,5595,3145,500,2070,86,92,15.1,48,6813,53 650 | University of New England,Yes,1209,750,265,19,54,820,159,11450,5045,900,2500,72,75,11.4,13,9718,64 651 | University of New Hampshire,No,9750,7640,2529,24,62,10358,1338,11180,3862,650,2450,89,87,17.5,16,7855,75 652 | University of North Carolina at Asheville,No,1757,979,394,32,74,2033,1078,5972,3420,600,750,77,83,13,11,7011,37 653 | University of North Carolina at Chapel Hill,No,14596,5985,3331,75,92,14609,1100,8400,4200,550,1200,88,93,8.9,23,15893,83 654 | University of North Carolina at Charlotte,No,5803,4441,1730,19,62,10099,3255,7248,3109,600,1900,79,91,16.8,7,6227,62 655 | University of North Carolina at Greensboro,No,5191,4134,1500,15,44,7532,1847,8677,3505,600,1300,75,94,15.5,17,7392,53 656 | University of North Carolina at Wilmington,No,6071,3856,1449,15,67,6635,1145,7558,3680,500,1500,82,85,19.1,15,6005,55 657 | University of North Dakota,No,2777,2249,1652,20,54,8334,1435,5634,2703,450,1200,97,97,15.9,16,9424,49 658 | University of North Florida,No,1800,1253,560,44,85,3876,3588,6634,4360,600,2604,82,85,17.8,14,6104,47 659 | University of North Texas,No,4418,2737,2049,23,51,14047,5134,4104,3579,450,1700,86,94,22.6,6,5657,35 660 | University of Northern Colorado,No,5530,4007,1697,12,37,8463,1498,7731,4128,540,2286,75,75,21.5,8,6309,40 661 | University of Northern Iowa,No,4144,3379,1853,18,52,10135,1448,6197,2930,595,2380,78,82,16.3,26,6333,77 662 | University of Notre Dame,Yes,7700,3700,1906,79,96,7671,30,16850,4400,600,1350,96,92,13.1,46,13936,97 663 | University of Oklahoma,No,4743,3970,2233,32,63,13436,2582,5173,3526,765,3176,86,90,11.5,11,10244,44 664 | University of Oregon,No,8631,6732,2546,25,61,11669,1605,10602,3660,570,1530,79,87,19.7,13,8020,54 665 | University of Pennsylvania,Yes,12394,5232,2464,85,100,9205,531,17020,7270,500,1544,95,96,6.3,38,25765,93 666 | University of Pittsburgh-Main Campus,No,8586,6383,2503,25,59,13138,4289,10786,4560,400,900,93,93,7.8,10,13789,66 667 | University of Portland,Yes,1758,1485,419,27,58,2041,174,12040,4100,600,1100,92,96,13.2,17,9060,72 668 | University of Puget Sound,Yes,4044,2826,688,51,83,2738,138,16230,4500,630,1800,79,86,15,17,11217,63 669 | University of Rhode Island,No,9643,7751,1968,12,40,8894,2456,10330,5558,500,1250,84,89,16.6,7,9158,63 670 | University of Richmond,Yes,5892,2718,756,46,72,2854,594,14500,3285,700,1125,75,89,11.7,32,11984,100 671 | University of Rochester,Yes,8766,5498,1243,56,75,5071,438,17840,6582,500,882,93,99,5.9,23,26037,80 672 | University of San Diego,Yes,3934,2735,886,40,70,3698,217,13600,5940,630,1820,93,96,15.6,13,10813,66 673 | University of San Francisco,Yes,2306,1721,538,23,48,4309,549,13226,6452,750,2450,86,86,13.6,8,10074,62 674 | University of Sci. and Arts of Oklahoma,No,285,280,208,21,43,1140,473,3687,1920,600,1800,67,77,23.6,3,3864,43 675 | University of Scranton,Yes,4471,2942,910,29,60,3674,493,11584,5986,650,800,83,83,14.1,41,9131,92 676 | University of South Carolina at Aiken,No,848,560,377,14,24,1855,1412,5800,3066,500,1500,62,62,14.8,3,5035,48 677 | University of South Carolina at Columbia,No,7693,5815,2328,30,66,12594,3661,8074,3522,495,2941,84,88,16.9,18,8246,63 678 | University of South Florida,No,7589,4676,1876,29,63,14770,10962,6760,3776,500,2180,84,89,17,7,11020,47 679 | University of Southern California,Yes,12229,8498,2477,45,71,13259,1429,17230,6482,600,2210,90,94,11.4,10,17007,68 680 | University of Southern Colorado,No,1401,1239,605,10,34,3716,675,7100,4380,540,2948,63,88,19.4,0,5389,36 681 | University of Southern Indiana,No,2379,2133,1292,8,25,4283,2973,4973,3192,500,1425,56,65,22,21,4078,38 682 | University of Southern Mississippi,No,2850,2044,1046,20,50,9260,1387,4652,2470,500,500,78,99,18.7,23,5917,45 683 | University of St. Thomas MN,Yes,2057,1807,828,26,53,4106,982,11712,4037,500,800,80,80,13.8,13,8546,89 684 | University of St. Thomas TX,Yes,374,280,185,45,77,995,408,8550,4050,500,1344,75,75,12.6,17,7237,62 685 | University of Tennessee at Knoxville,No,7473,5372,3013,27,53,15749,3237,5764,3262,750,3300,86,92,16.5,22,8612,53 686 | University of Texas at Arlington,No,3281,2559,1448,19,43,10975,8431,4422,2780,500,2850,73,73,21,4,4696,29 687 | University of Texas at Austin,No,14752,9572,5329,48,85,30017,5189,5130,3309,650,3140,91,99,19.7,11,7837,65 688 | University of Texas at San Antonio,No,4217,3100,1686,17,46,9375,5457,4104,5376,452,1200,94,100,25.3,3,4329,50 689 | University of the Arts,Yes,974,704,290,5,22,1145,39,12520,3860,1300,700,16,59,7.5,9,11641,57 690 | University of the Pacific,Yes,2459,1997,582,36,66,2664,299,16320,5326,646,1171,87,94,11.2,14,13706,65 691 | University of the South,Yes,1445,966,326,46,83,1129,24,15350,4080,450,810,89,93,10.3,52,18784,82 692 | University of Tulsa,Yes,1712,1557,696,41,68,2936,433,11750,4160,1200,2350,94,96,11.5,10,11743,47 693 | University of Utah,No,5095,4491,2400,27,53,13894,8374,6857,3975,858,3093,89,93,12.8,9,9275,37 694 | University of Vermont,No,7663,6008,1735,18,51,7353,1674,15516,4928,500,990,87,90,9.9,10,12646,79 695 | University of Virginia,No,15849,5384,2678,74,95,11278,114,12212,3792,500,1000,90,92,9.5,22,13597,95 696 | University of Washington,No,12749,7025,3343,40,81,20356,4582,8199,4218,708,2172,96,94,9,10,16527,65 697 | University of West Florida,No,1558,1254,472,20,57,3754,2477,6172,3994,541,1387,83,87,23.4,12,8488,53 698 | University of Wisconsin-Stout,No,2593,1966,1030,9,32,6038,579,6704,2592,376,1750,78,78,21,17,6254,65 699 | University of Wisconsin-Superior,No,910,910,342,14,53,1434,417,7032,2780,550,1960,75,81,15.2,15,6490,36 700 | University of Wisconsin-Whitewater,No,4400,3719,1472,12,38,7804,1552,6950,2500,300,1200,90,95,23.1,16,5559,67 701 | University of Wisconsin at Green Bay,No,2409,1939,759,17,50,3819,1347,6900,2800,475,1200,81,89,22.2,1,5968,46 702 | University of Wisconsin at Madison,No,14901,10932,4631,36,80,23945,2200,9096,4290,535,1545,93,96,11.5,20,11006,72 703 | University of Wisconsin at Milwaukee,No,5244,3782,1930,12,37,11561,7443,8786,2964,570,1980,79,87,15.9,8,8094,38 704 | University of Wyoming,No,2029,1516,1073,23,46,7535,1488,5988,3422,600,1500,91,94,15.1,13,8745,45 705 | Upper Iowa University,Yes,663,452,192,10,35,1481,1160,8840,3060,500,1000,69,75,17.4,19,3733,78 706 | Ursinus College,Yes,1399,1026,308,44,77,1131,17,14900,5160,500,800,82,85,11.6,40,12082,79 707 | Ursuline College,Yes,325,260,86,21,47,699,717,9600,4202,450,750,39,69,10.5,15,7164,68 708 | Valley City State University,No,368,344,212,5,27,863,189,4286,2570,600,2000,39,41,14.9,25,4958,40 709 | Valparaiso University,Yes,2075,1727,520,49,81,2501,198,11800,3260,500,800,87,89,14.2,23,9681,95 710 | Vanderbilt University,Yes,7791,4690,1499,71,92,5500,90,17865,6525,630,952,93,98,5.8,26,23850,83 711 | Vassar College,Yes,3550,1877,653,53,87,2164,77,18920,5950,600,800,90,98,9.7,39,17089,90 712 | Villanova University,Yes,7759,5588,1477,30,68,6362,1292,15925,6507,400,300,89,90,13.4,24,10458,96 713 | Virginia Commonwealth University,No,4963,3497,1567,18,45,10262,5065,10217,4182,500,3630,81,87,8.7,11,11183,45 714 | Virginia State University,No,2996,2440,704,2,30,3006,338,5587,4845,500,600,61,63,16,11,5733,31 715 | Virginia Tech,No,15712,11719,4277,29,53,18511,604,10260,3176,740,2200,85,89,13.8,20,8944,73 716 | Virginia Union University,Yes,1847,1610,453,19,59,1298,67,7384,3494,500,1763,51,67,13.7,8,6757,30 717 | Virginia Wesleyan College,Yes,1470,900,287,20,49,1130,417,10900,5100,500,550,70,81,15.7,14,7804,68 718 | Viterbo College,Yes,647,518,271,17,43,1014,387,9140,3365,500,2245,51,65,10.7,31,8050,73 719 | Voorhees College,Yes,1465,1006,188,10,30,703,20,4450,2522,500,1200,43,43,22.9,3,5861,58 720 | Wabash College,Yes,800,623,256,41,76,801,5,12925,4195,500,635,78,85,9.9,55,14904,72 721 | Wagner College,Yes,1416,1015,417,10,44,1324,117,13500,5800,585,1700,67,78,13.2,23,9006,75 722 | Wake Forest University,Yes,5661,2392,903,75,88,3499,172,13850,4360,500,1250,95,97,4.3,37,41766,89 723 | Walsh University,Yes,1092,890,477,27,92,847,497,8670,4180,500,1450,42,58,11.3,33,5738,68 724 | Warren Wilson College,Yes,440,311,112,25,49,466,7,10000,3052,400,1100,65,75,11.4,20,9430,63 725 | Wartburg College,Yes,1231,1074,345,34,66,1295,105,11600,3610,400,850,66,91,12.4,37,7735,67 726 | Washington and Jefferson College,Yes,1305,1100,334,42,64,1098,151,16260,4005,300,500,91,91,12.1,40,10162,86 727 | Washington and Lee University,Yes,3315,1096,425,68,93,1584,3,13750,4619,680,1115,81,96,9.6,45,15736,90 728 | Washington College,Yes,1209,942,214,31,60,822,46,15276,5318,500,300,79,86,11.2,37,10830,65 729 | Washington State University,No,6540,5839,2440,31,70,14445,1344,8200,4210,800,2719,84,87,16.9,30,10912,56 730 | Washington University,Yes,7654,5259,1254,62,93,4879,1274,18350,5775,768,1512,91,98,3.9,31,45702,90 731 | Wayne State College,No,1373,1373,724,6,21,2754,474,2700,2660,540,1660,60,68,20.3,29,4550,52 732 | Waynesburg College,Yes,1190,978,324,12,30,1280,61,8840,3620,500,1200,57,58,16.2,26,6563,63 733 | Webber College,Yes,280,143,79,5,27,327,110,5590,2900,650,1952,53,63,15.1,4,4839,90 734 | Webster University,Yes,665,462,226,17,44,1739,1550,9160,4340,500,500,68,68,20.6,14,6951,48 735 | Wellesley College,Yes,2895,1249,579,80,96,2195,156,18345,5995,500,700,94,98,10.6,51,21409,91 736 | Wells College,Yes,318,240,130,40,85,416,19,14900,5550,600,500,93,98,8.3,42,13935,69 737 | Wentworth Institute of Technology,Yes,1480,1257,452,6,25,2961,572,9850,6050,850,920,10,68,15.4,8,17858,64 738 | Wesley College,Yes,980,807,350,10,25,872,448,9890,4674,500,1350,52,57,14.4,15,6243,84 739 | Wesleyan University,Yes,4772,1973,712,60,86,2714,27,19130,5600,1400,1400,90,94,12.1,39,16262,92 740 | West Chester University of Penn.,No,6502,3539,1372,11,51,7484,1904,7844,4108,400,2000,76,79,15.3,16,6773,52 741 | West Liberty State College,No,1164,1062,478,12,25,2138,227,4470,2890,600,1210,33,33,16.3,10,4249,60 742 | West Virginia Wesleyan College,Yes,1566,1400,483,28,55,1509,170,14200,3775,450,1100,58,81,16.4,42,8080,67 743 | Western Carolina University,No,3224,2519,1057,11,31,5000,706,6390,2380,110,1622,67,78,14.6,9,6554,55 744 | Western Maryland College,Yes,1205,984,278,31,50,1071,98,14510,5340,500,1400,84,91,12.5,39,10026,60 745 | Western Michigan University,No,9167,7191,2738,24,53,15739,4278,6940,4100,500,1700,80,84,24.7,11,5983,55 746 | Western New England College,Yes,1650,1471,409,7,21,1803,1116,8994,5500,498,2065,74,97,15.4,15,8409,59 747 | Western State College of Colorado,No,2702,1623,604,7,24,2315,146,5918,3755,500,2050,76,79,19.4,4,4599,52 748 | Western Washington University,No,5548,3563,1549,30,71,8909,506,8124,4144,639,2385,83,89,22.7,10,7203,61 749 | Westfield State College,No,3100,2150,825,3,20,3234,941,5542,3788,500,1300,75,79,15.7,20,4222,65 750 | Westminster College MO,Yes,662,553,184,20,43,665,37,10720,4050,600,1650,66,70,12.5,20,7925,62 751 | Westminster College,Yes,996,866,377,29,58,1411,72,12065,3615,430,685,62,78,12.5,41,8596,80 752 | Westminster College of Salt Lake City,Yes,917,720,213,21,60,979,743,8820,4050,600,2025,68,83,10.5,34,7170,50 753 | Westmont College,No,950,713,351,42,72,1276,9,14320,5304,490,1410,77,77,14.9,17,8837,87 754 | Wheaton College IL,Yes,1432,920,548,56,84,2200,56,11480,4200,530,1400,81,83,12.7,40,11916,85 755 | Westminster College PA,Yes,1738,1373,417,21,55,1335,30,18460,5970,700,850,92,96,13.2,41,22704,71 756 | Wheeling Jesuit College,Yes,903,755,213,15,49,971,305,10500,4545,600,600,66,71,14.1,27,7494,72 757 | Whitman College,Yes,1861,998,359,45,77,1220,46,16670,4900,750,800,80,83,10.5,51,13198,72 758 | Whittier College,Yes,1681,1069,344,35,63,1235,30,16249,5699,500,1998,84,92,13.6,29,11778,52 759 | Whitworth College,Yes,1121,926,372,43,70,1270,160,12660,4500,678,2424,80,80,16.9,20,8328,80 760 | Widener University,Yes,2139,1492,502,24,64,2186,2171,12350,5370,500,1350,88,86,12.6,19,9603,63 761 | Wilkes University,Yes,1631,1431,434,15,36,1803,603,11150,5130,550,1260,78,92,13.3,24,8543,67 762 | Willamette University,Yes,1658,1327,395,49,80,1595,159,14800,4620,400,790,91,94,13.3,37,10779,68 763 | William Jewell College,Yes,663,547,315,32,67,1279,75,10060,2970,500,2600,74,80,11.2,19,7885,59 764 | William Woods University,Yes,469,435,227,17,39,851,120,10535,4365,550,3700,39,66,12.9,16,7438,52 765 | Williams College,Yes,4186,1245,526,81,96,1988,29,19629,5790,500,1200,94,99,9,64,22014,99 766 | Wilson College,Yes,167,130,46,16,50,199,676,11428,5084,450,475,67,76,8.3,43,10291,67 767 | Wingate College,Yes,1239,1017,383,10,34,1207,157,7820,3400,550,1550,69,81,13.9,8,7264,91 768 | Winona State University,No,3325,2047,1301,20,45,5800,872,4200,2700,300,1200,53,60,20.2,18,5318,58 769 | Winthrop University,No,2320,1805,769,24,61,3395,670,6400,3392,580,2150,71,80,12.8,26,6729,59 770 | Wisconsin Lutheran College,Yes,152,128,75,17,41,282,22,9100,3700,500,1400,48,48,8.5,26,8960,50 771 | Wittenberg University,Yes,1979,1739,575,42,68,1980,144,15948,4404,400,800,82,95,12.8,29,10414,78 772 | Wofford College,Yes,1501,935,273,51,83,1059,34,12680,4150,605,1440,91,92,15.3,42,7875,75 773 | Worcester Polytechnic Institute,Yes,2768,2314,682,49,86,2802,86,15884,5370,530,730,92,94,15.2,34,10774,82 774 | Worcester State College,No,2197,1515,543,4,26,3089,2029,6797,3900,500,1200,60,60,21,14,4469,40 775 | Xavier University,Yes,1959,1805,695,24,47,2849,1107,11520,4960,600,1250,73,75,13.3,31,9189,83 776 | Xavier University of Louisiana,Yes,2097,1915,695,34,61,2793,166,6900,4200,617,781,67,75,14.4,20,8323,49 777 | Yale University,Yes,10705,2453,1317,95,99,5217,83,19840,6510,630,2115,96,96,5.8,49,40386,99 778 | York College of Pennsylvania,Yes,2989,1855,691,28,63,2988,1726,4990,3560,500,1250,75,75,18.1,28,4509,99 779 | -------------------------------------------------------------------------------- /Data/Credit.csv: -------------------------------------------------------------------------------- 1 | "","Income","Limit","Rating","Cards","Age","Education","Gender","Student","Married","Ethnicity","Balance" 2 | "1",14.891,3606,283,2,34,11," Male","No","Yes","Caucasian",333 3 | 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101 | "100",83.851,8494,607,5,47,18," Male","No","No","Caucasian",1311 102 | "101",21.153,3736,256,1,41,11," Male","No","No","Caucasian",298 103 | "102",17.976,2433,190,3,70,16,"Female","Yes","No","Caucasian",431 104 | "103",68.713,7582,531,2,56,16," Male","Yes","No","Caucasian",1587 105 | "104",146.183,9540,682,6,66,15," Male","No","No","Caucasian",1050 106 | "105",15.846,4768,365,4,53,12,"Female","No","No","Caucasian",745 107 | "106",12.031,3182,259,2,58,18,"Female","No","Yes","Caucasian",210 108 | "107",16.819,1337,115,2,74,15," Male","No","Yes","Asian",0 109 | "108",39.11,3189,263,3,72,12," Male","No","No","Asian",0 110 | "109",107.986,6033,449,4,64,14," Male","No","Yes","Caucasian",227 111 | "110",13.561,3261,279,5,37,19," Male","No","Yes","Asian",297 112 | "111",34.537,3271,250,3,57,17,"Female","No","Yes","Asian",47 113 | "112",28.575,2959,231,2,60,11,"Female","No","No","African American",0 114 | "113",46.007,6637,491,4,42,14," Male","No","Yes","Caucasian",1046 115 | 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"128",57.202,3411,259,3,72,11,"Female","No","No","Caucasian",0 130 | "129",123.299,8376,610,2,89,17," Male","Yes","No","African American",1259 131 | "130",18.145,3461,279,3,56,15," Male","No","Yes","African American",255 132 | "131",23.793,3821,281,4,56,12,"Female","Yes","Yes","African American",868 133 | "132",10.726,1568,162,5,46,19," Male","No","Yes","Asian",0 134 | "133",23.283,5443,407,4,49,13," Male","No","Yes","African American",912 135 | "134",21.455,5829,427,4,80,12,"Female","No","Yes","African American",1018 136 | "135",34.664,5835,452,3,77,15,"Female","No","Yes","African American",835 137 | "136",44.473,3500,257,3,81,16,"Female","No","No","African American",8 138 | "137",54.663,4116,314,2,70,8,"Female","No","No","African American",75 139 | "138",36.355,3613,278,4,35,9," Male","No","Yes","Asian",187 140 | "139",21.374,2073,175,2,74,11,"Female","No","Yes","Caucasian",0 141 | "140",107.841,10384,728,3,87,7," Male","No","No","African American",1597 142 | 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Male","No","No","African American",230 211 | "210",151.947,9156,642,2,91,11,"Female","No","Yes","African American",732 212 | "211",24.543,3206,243,2,62,12,"Female","No","Yes","Caucasian",95 213 | "212",29.567,5309,397,3,25,15," Male","No","No","Caucasian",799 214 | "213",39.145,4351,323,2,66,13," Male","No","Yes","Caucasian",308 215 | "214",39.422,5245,383,2,44,19," Male","No","No","African American",637 216 | "215",34.909,5289,410,2,62,16,"Female","No","Yes","Caucasian",681 217 | "216",41.025,4229,337,3,79,19,"Female","No","Yes","Caucasian",246 218 | "217",15.476,2762,215,3,60,18," Male","No","No","Asian",52 219 | "218",12.456,5395,392,3,65,14," Male","No","Yes","Caucasian",955 220 | "219",10.627,1647,149,2,71,10,"Female","Yes","Yes","Asian",195 221 | "220",38.954,5222,370,4,76,13,"Female","No","No","Caucasian",653 222 | "221",44.847,5765,437,3,53,13,"Female","Yes","No","Asian",1246 223 | "222",98.515,8760,633,5,78,11,"Female","No","No","African American",1230 224 | 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Male","No","No","Caucasian",1192 350 | "349",13.433,1134,112,3,70,14," Male","No","Yes","Caucasian",0 351 | "350",48.577,5145,389,3,71,13,"Female","No","Yes","Asian",503 352 | "351",30.002,1561,155,4,70,13,"Female","No","Yes","Caucasian",0 353 | "352",61.62,5140,374,1,71,9," Male","No","Yes","Caucasian",302 354 | "353",104.483,7140,507,2,41,14," Male","No","Yes","African American",583 355 | "354",41.868,4716,342,2,47,18," Male","No","No","Caucasian",425 356 | "355",12.068,3873,292,1,44,18,"Female","No","Yes","Asian",413 357 | "356",180.682,11966,832,2,58,8,"Female","No","Yes","African American",1405 358 | "357",34.48,6090,442,3,36,14," Male","No","No","Caucasian",962 359 | "358",39.609,2539,188,1,40,14," Male","No","Yes","Asian",0 360 | "359",30.111,4336,339,1,81,18," Male","No","Yes","Caucasian",347 361 | "360",12.335,4471,344,3,79,12," Male","No","Yes","African American",611 362 | "361",53.566,5891,434,4,82,10,"Female","No","No","Caucasian",712 363 | 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"376",20.974,5673,413,5,44,16,"Female","No","Yes","Caucasian",1000 378 | "377",87.625,7167,515,2,46,10,"Female","No","No","African American",767 379 | "378",28.144,1567,142,3,51,10," Male","No","Yes","Caucasian",0 380 | "379",19.349,4941,366,1,33,19," Male","No","Yes","Caucasian",717 381 | "380",53.308,2860,214,1,84,10," Male","No","Yes","Caucasian",0 382 | "381",115.123,7760,538,3,83,14,"Female","No","No","African American",661 383 | "382",101.788,8029,574,2,84,11," Male","No","Yes","Caucasian",849 384 | "383",24.824,5495,409,1,33,9," Male","Yes","No","Caucasian",1352 385 | "384",14.292,3274,282,9,64,9," Male","No","Yes","Caucasian",382 386 | "385",20.088,1870,180,3,76,16," Male","No","No","African American",0 387 | "386",26.4,5640,398,3,58,15,"Female","No","No","Asian",905 388 | "387",19.253,3683,287,4,57,10," Male","No","No","African American",371 389 | "388",16.529,1357,126,3,62,9," Male","No","No","Asian",0 390 | "389",37.878,6827,482,2,80,13,"Female","No","No","Caucasian",1129 391 | "390",83.948,7100,503,2,44,18," Male","No","No","Caucasian",806 392 | "391",135.118,10578,747,3,81,15,"Female","No","Yes","Asian",1393 393 | "392",73.327,6555,472,2,43,15,"Female","No","No","Caucasian",721 394 | "393",25.974,2308,196,2,24,10," Male","No","No","Asian",0 395 | "394",17.316,1335,138,2,65,13," Male","No","No","African American",0 396 | "395",49.794,5758,410,4,40,8," Male","No","No","Caucasian",734 397 | "396",12.096,4100,307,3,32,13," Male","No","Yes","Caucasian",560 398 | "397",13.364,3838,296,5,65,17," Male","No","No","African American",480 399 | "398",57.872,4171,321,5,67,12,"Female","No","Yes","Caucasian",138 400 | "399",37.728,2525,192,1,44,13," Male","No","Yes","Caucasian",0 401 | "400",18.701,5524,415,5,64,7,"Female","No","No","Asian",966 402 | -------------------------------------------------------------------------------- /Data/Heart.csv: -------------------------------------------------------------------------------- 1 | "","Age","Sex","ChestPain","RestBP","Chol","Fbs","RestECG","MaxHR","ExAng","Oldpeak","Slope","Ca","Thal","AHD" 2 | "1",63,1,"typical",145,233,1,2,150,0,2.3,3,0,"fixed","No" 3 | "2",67,1,"asymptomatic",160,286,0,2,108,1,1.5,2,3,"normal","Yes" 4 | "3",67,1,"asymptomatic",120,229,0,2,129,1,2.6,2,2,"reversable","Yes" 5 | "4",37,1,"nonanginal",130,250,0,0,187,0,3.5,3,0,"normal","No" 6 | "5",41,0,"nontypical",130,204,0,2,172,0,1.4,1,0,"normal","No" 7 | "6",56,1,"nontypical",120,236,0,0,178,0,0.8,1,0,"normal","No" 8 | "7",62,0,"asymptomatic",140,268,0,2,160,0,3.6,3,2,"normal","Yes" 9 | "8",57,0,"asymptomatic",120,354,0,0,163,1,0.6,1,0,"normal","No" 10 | "9",63,1,"asymptomatic",130,254,0,2,147,0,1.4,2,1,"reversable","Yes" 11 | "10",53,1,"asymptomatic",140,203,1,2,155,1,3.1,3,0,"reversable","Yes" 12 | "11",57,1,"asymptomatic",140,192,0,0,148,0,0.4,2,0,"fixed","No" 13 | "12",56,0,"nontypical",140,294,0,2,153,0,1.3,2,0,"normal","No" 14 | "13",56,1,"nonanginal",130,256,1,2,142,1,0.6,2,1,"fixed","Yes" 15 | "14",44,1,"nontypical",120,263,0,0,173,0,0,1,0,"reversable","No" 16 | "15",52,1,"nonanginal",172,199,1,0,162,0,0.5,1,0,"reversable","No" 17 | "16",57,1,"nonanginal",150,168,0,0,174,0,1.6,1,0,"normal","No" 18 | "17",48,1,"nontypical",110,229,0,0,168,0,1,3,0,"reversable","Yes" 19 | "18",54,1,"asymptomatic",140,239,0,0,160,0,1.2,1,0,"normal","No" 20 | "19",48,0,"nonanginal",130,275,0,0,139,0,0.2,1,0,"normal","No" 21 | "20",49,1,"nontypical",130,266,0,0,171,0,0.6,1,0,"normal","No" 22 | "21",64,1,"typical",110,211,0,2,144,1,1.8,2,0,"normal","No" 23 | "22",58,0,"typical",150,283,1,2,162,0,1,1,0,"normal","No" 24 | "23",58,1,"nontypical",120,284,0,2,160,0,1.8,2,0,"normal","Yes" 25 | "24",58,1,"nonanginal",132,224,0,2,173,0,3.2,1,2,"reversable","Yes" 26 | "25",60,1,"asymptomatic",130,206,0,2,132,1,2.4,2,2,"reversable","Yes" 27 | "26",50,0,"nonanginal",120,219,0,0,158,0,1.6,2,0,"normal","No" 28 | "27",58,0,"nonanginal",120,340,0,0,172,0,0,1,0,"normal","No" 29 | "28",66,0,"typical",150,226,0,0,114,0,2.6,3,0,"normal","No" 30 | "29",43,1,"asymptomatic",150,247,0,0,171,0,1.5,1,0,"normal","No" 31 | "30",40,1,"asymptomatic",110,167,0,2,114,1,2,2,0,"reversable","Yes" 32 | "31",69,0,"typical",140,239,0,0,151,0,1.8,1,2,"normal","No" 33 | "32",60,1,"asymptomatic",117,230,1,0,160,1,1.4,1,2,"reversable","Yes" 34 | "33",64,1,"nonanginal",140,335,0,0,158,0,0,1,0,"normal","Yes" 35 | "34",59,1,"asymptomatic",135,234,0,0,161,0,0.5,2,0,"reversable","No" 36 | "35",44,1,"nonanginal",130,233,0,0,179,1,0.4,1,0,"normal","No" 37 | "36",42,1,"asymptomatic",140,226,0,0,178,0,0,1,0,"normal","No" 38 | "37",43,1,"asymptomatic",120,177,0,2,120,1,2.5,2,0,"reversable","Yes" 39 | "38",57,1,"asymptomatic",150,276,0,2,112,1,0.6,2,1,"fixed","Yes" 40 | "39",55,1,"asymptomatic",132,353,0,0,132,1,1.2,2,1,"reversable","Yes" 41 | "40",61,1,"nonanginal",150,243,1,0,137,1,1,2,0,"normal","No" 42 | "41",65,0,"asymptomatic",150,225,0,2,114,0,1,2,3,"reversable","Yes" 43 | "42",40,1,"typical",140,199,0,0,178,1,1.4,1,0,"reversable","No" 44 | "43",71,0,"nontypical",160,302,0,0,162,0,0.4,1,2,"normal","No" 45 | "44",59,1,"nonanginal",150,212,1,0,157,0,1.6,1,0,"normal","No" 46 | "45",61,0,"asymptomatic",130,330,0,2,169,0,0,1,0,"normal","Yes" 47 | "46",58,1,"nonanginal",112,230,0,2,165,0,2.5,2,1,"reversable","Yes" 48 | "47",51,1,"nonanginal",110,175,0,0,123,0,0.6,1,0,"normal","No" 49 | "48",50,1,"asymptomatic",150,243,0,2,128,0,2.6,2,0,"reversable","Yes" 50 | "49",65,0,"nonanginal",140,417,1,2,157,0,0.8,1,1,"normal","No" 51 | "50",53,1,"nonanginal",130,197,1,2,152,0,1.2,3,0,"normal","No" 52 | "51",41,0,"nontypical",105,198,0,0,168,0,0,1,1,"normal","No" 53 | "52",65,1,"asymptomatic",120,177,0,0,140,0,0.4,1,0,"reversable","No" 54 | "53",44,1,"asymptomatic",112,290,0,2,153,0,0,1,1,"normal","Yes" 55 | "54",44,1,"nontypical",130,219,0,2,188,0,0,1,0,"normal","No" 56 | "55",60,1,"asymptomatic",130,253,0,0,144,1,1.4,1,1,"reversable","Yes" 57 | "56",54,1,"asymptomatic",124,266,0,2,109,1,2.2,2,1,"reversable","Yes" 58 | "57",50,1,"nonanginal",140,233,0,0,163,0,0.6,2,1,"reversable","Yes" 59 | "58",41,1,"asymptomatic",110,172,0,2,158,0,0,1,0,"reversable","Yes" 60 | "59",54,1,"nonanginal",125,273,0,2,152,0,0.5,3,1,"normal","No" 61 | "60",51,1,"typical",125,213,0,2,125,1,1.4,1,1,"normal","No" 62 | "61",51,0,"asymptomatic",130,305,0,0,142,1,1.2,2,0,"reversable","Yes" 63 | "62",46,0,"nonanginal",142,177,0,2,160,1,1.4,3,0,"normal","No" 64 | "63",58,1,"asymptomatic",128,216,0,2,131,1,2.2,2,3,"reversable","Yes" 65 | "64",54,0,"nonanginal",135,304,1,0,170,0,0,1,0,"normal","No" 66 | "65",54,1,"asymptomatic",120,188,0,0,113,0,1.4,2,1,"reversable","Yes" 67 | "66",60,1,"asymptomatic",145,282,0,2,142,1,2.8,2,2,"reversable","Yes" 68 | "67",60,1,"nonanginal",140,185,0,2,155,0,3,2,0,"normal","Yes" 69 | "68",54,1,"nonanginal",150,232,0,2,165,0,1.6,1,0,"reversable","No" 70 | "69",59,1,"asymptomatic",170,326,0,2,140,1,3.4,3,0,"reversable","Yes" 71 | "70",46,1,"nonanginal",150,231,0,0,147,0,3.6,2,0,"normal","Yes" 72 | "71",65,0,"nonanginal",155,269,0,0,148,0,0.8,1,0,"normal","No" 73 | "72",67,1,"asymptomatic",125,254,1,0,163,0,0.2,2,2,"reversable","Yes" 74 | "73",62,1,"asymptomatic",120,267,0,0,99,1,1.8,2,2,"reversable","Yes" 75 | "74",65,1,"asymptomatic",110,248,0,2,158,0,0.6,1,2,"fixed","Yes" 76 | "75",44,1,"asymptomatic",110,197,0,2,177,0,0,1,1,"normal","Yes" 77 | "76",65,0,"nonanginal",160,360,0,2,151,0,0.8,1,0,"normal","No" 78 | "77",60,1,"asymptomatic",125,258,0,2,141,1,2.8,2,1,"reversable","Yes" 79 | "78",51,0,"nonanginal",140,308,0,2,142,0,1.5,1,1,"normal","No" 80 | "79",48,1,"nontypical",130,245,0,2,180,0,0.2,2,0,"normal","No" 81 | "80",58,1,"asymptomatic",150,270,0,2,111,1,0.8,1,0,"reversable","Yes" 82 | "81",45,1,"asymptomatic",104,208,0,2,148,1,3,2,0,"normal","No" 83 | "82",53,0,"asymptomatic",130,264,0,2,143,0,0.4,2,0,"normal","No" 84 | "83",39,1,"nonanginal",140,321,0,2,182,0,0,1,0,"normal","No" 85 | "84",68,1,"nonanginal",180,274,1,2,150,1,1.6,2,0,"reversable","Yes" 86 | "85",52,1,"nontypical",120,325,0,0,172,0,0.2,1,0,"normal","No" 87 | "86",44,1,"nonanginal",140,235,0,2,180,0,0,1,0,"normal","No" 88 | "87",47,1,"nonanginal",138,257,0,2,156,0,0,1,0,"normal","No" 89 | "88",53,0,"nonanginal",128,216,0,2,115,0,0,1,0,NA,"No" 90 | "89",53,0,"asymptomatic",138,234,0,2,160,0,0,1,0,"normal","No" 91 | "90",51,0,"nonanginal",130,256,0,2,149,0,0.5,1,0,"normal","No" 92 | "91",66,1,"asymptomatic",120,302,0,2,151,0,0.4,2,0,"normal","No" 93 | "92",62,0,"asymptomatic",160,164,0,2,145,0,6.2,3,3,"reversable","Yes" 94 | "93",62,1,"nonanginal",130,231,0,0,146,0,1.8,2,3,"reversable","No" 95 | "94",44,0,"nonanginal",108,141,0,0,175,0,0.6,2,0,"normal","No" 96 | "95",63,0,"nonanginal",135,252,0,2,172,0,0,1,0,"normal","No" 97 | "96",52,1,"asymptomatic",128,255,0,0,161,1,0,1,1,"reversable","Yes" 98 | "97",59,1,"asymptomatic",110,239,0,2,142,1,1.2,2,1,"reversable","Yes" 99 | "98",60,0,"asymptomatic",150,258,0,2,157,0,2.6,2,2,"reversable","Yes" 100 | "99",52,1,"nontypical",134,201,0,0,158,0,0.8,1,1,"normal","No" 101 | "100",48,1,"asymptomatic",122,222,0,2,186,0,0,1,0,"normal","No" 102 | "101",45,1,"asymptomatic",115,260,0,2,185,0,0,1,0,"normal","No" 103 | "102",34,1,"typical",118,182,0,2,174,0,0,1,0,"normal","No" 104 | "103",57,0,"asymptomatic",128,303,0,2,159,0,0,1,1,"normal","No" 105 | "104",71,0,"nonanginal",110,265,1,2,130,0,0,1,1,"normal","No" 106 | "105",49,1,"nonanginal",120,188,0,0,139,0,2,2,3,"reversable","Yes" 107 | "106",54,1,"nontypical",108,309,0,0,156,0,0,1,0,"reversable","No" 108 | "107",59,1,"asymptomatic",140,177,0,0,162,1,0,1,1,"reversable","Yes" 109 | "108",57,1,"nonanginal",128,229,0,2,150,0,0.4,2,1,"reversable","Yes" 110 | "109",61,1,"asymptomatic",120,260,0,0,140,1,3.6,2,1,"reversable","Yes" 111 | "110",39,1,"asymptomatic",118,219,0,0,140,0,1.2,2,0,"reversable","Yes" 112 | "111",61,0,"asymptomatic",145,307,0,2,146,1,1,2,0,"reversable","Yes" 113 | "112",56,1,"asymptomatic",125,249,1,2,144,1,1.2,2,1,"normal","Yes" 114 | "113",52,1,"typical",118,186,0,2,190,0,0,2,0,"fixed","No" 115 | "114",43,0,"asymptomatic",132,341,1,2,136,1,3,2,0,"reversable","Yes" 116 | "115",62,0,"nonanginal",130,263,0,0,97,0,1.2,2,1,"reversable","Yes" 117 | "116",41,1,"nontypical",135,203,0,0,132,0,0,2,0,"fixed","No" 118 | "117",58,1,"nonanginal",140,211,1,2,165,0,0,1,0,"normal","No" 119 | "118",35,0,"asymptomatic",138,183,0,0,182,0,1.4,1,0,"normal","No" 120 | "119",63,1,"asymptomatic",130,330,1,2,132,1,1.8,1,3,"reversable","Yes" 121 | "120",65,1,"asymptomatic",135,254,0,2,127,0,2.8,2,1,"reversable","Yes" 122 | "121",48,1,"asymptomatic",130,256,1,2,150,1,0,1,2,"reversable","Yes" 123 | "122",63,0,"asymptomatic",150,407,0,2,154,0,4,2,3,"reversable","Yes" 124 | "123",51,1,"nonanginal",100,222,0,0,143,1,1.2,2,0,"normal","No" 125 | "124",55,1,"asymptomatic",140,217,0,0,111,1,5.6,3,0,"reversable","Yes" 126 | "125",65,1,"typical",138,282,1,2,174,0,1.4,2,1,"normal","Yes" 127 | "126",45,0,"nontypical",130,234,0,2,175,0,0.6,2,0,"normal","No" 128 | "127",56,0,"asymptomatic",200,288,1,2,133,1,4,3,2,"reversable","Yes" 129 | "128",54,1,"asymptomatic",110,239,0,0,126,1,2.8,2,1,"reversable","Yes" 130 | "129",44,1,"nontypical",120,220,0,0,170,0,0,1,0,"normal","No" 131 | "130",62,0,"asymptomatic",124,209,0,0,163,0,0,1,0,"normal","No" 132 | "131",54,1,"nonanginal",120,258,0,2,147,0,0.4,2,0,"reversable","No" 133 | "132",51,1,"nonanginal",94,227,0,0,154,1,0,1,1,"reversable","No" 134 | "133",29,1,"nontypical",130,204,0,2,202,0,0,1,0,"normal","No" 135 | "134",51,1,"asymptomatic",140,261,0,2,186,1,0,1,0,"normal","No" 136 | "135",43,0,"nonanginal",122,213,0,0,165,0,0.2,2,0,"normal","No" 137 | "136",55,0,"nontypical",135,250,0,2,161,0,1.4,2,0,"normal","No" 138 | "137",70,1,"asymptomatic",145,174,0,0,125,1,2.6,3,0,"reversable","Yes" 139 | "138",62,1,"nontypical",120,281,0,2,103,0,1.4,2,1,"reversable","Yes" 140 | "139",35,1,"asymptomatic",120,198,0,0,130,1,1.6,2,0,"reversable","Yes" 141 | "140",51,1,"nonanginal",125,245,1,2,166,0,2.4,2,0,"normal","No" 142 | "141",59,1,"nontypical",140,221,0,0,164,1,0,1,0,"normal","No" 143 | "142",59,1,"typical",170,288,0,2,159,0,0.2,2,0,"reversable","Yes" 144 | "143",52,1,"nontypical",128,205,1,0,184,0,0,1,0,"normal","No" 145 | "144",64,1,"nonanginal",125,309,0,0,131,1,1.8,2,0,"reversable","Yes" 146 | "145",58,1,"nonanginal",105,240,0,2,154,1,0.6,2,0,"reversable","No" 147 | "146",47,1,"nonanginal",108,243,0,0,152,0,0,1,0,"normal","Yes" 148 | "147",57,1,"asymptomatic",165,289,1,2,124,0,1,2,3,"reversable","Yes" 149 | "148",41,1,"nonanginal",112,250,0,0,179,0,0,1,0,"normal","No" 150 | "149",45,1,"nontypical",128,308,0,2,170,0,0,1,0,"normal","No" 151 | "150",60,0,"nonanginal",102,318,0,0,160,0,0,1,1,"normal","No" 152 | "151",52,1,"typical",152,298,1,0,178,0,1.2,2,0,"reversable","No" 153 | "152",42,0,"asymptomatic",102,265,0,2,122,0,0.6,2,0,"normal","No" 154 | "153",67,0,"nonanginal",115,564,0,2,160,0,1.6,2,0,"reversable","No" 155 | "154",55,1,"asymptomatic",160,289,0,2,145,1,0.8,2,1,"reversable","Yes" 156 | "155",64,1,"asymptomatic",120,246,0,2,96,1,2.2,3,1,"normal","Yes" 157 | "156",70,1,"asymptomatic",130,322,0,2,109,0,2.4,2,3,"normal","Yes" 158 | "157",51,1,"asymptomatic",140,299,0,0,173,1,1.6,1,0,"reversable","Yes" 159 | "158",58,1,"asymptomatic",125,300,0,2,171,0,0,1,2,"reversable","Yes" 160 | "159",60,1,"asymptomatic",140,293,0,2,170,0,1.2,2,2,"reversable","Yes" 161 | "160",68,1,"nonanginal",118,277,0,0,151,0,1,1,1,"reversable","No" 162 | "161",46,1,"nontypical",101,197,1,0,156,0,0,1,0,"reversable","No" 163 | "162",77,1,"asymptomatic",125,304,0,2,162,1,0,1,3,"normal","Yes" 164 | "163",54,0,"nonanginal",110,214,0,0,158,0,1.6,2,0,"normal","No" 165 | "164",58,0,"asymptomatic",100,248,0,2,122,0,1,2,0,"normal","No" 166 | "165",48,1,"nonanginal",124,255,1,0,175,0,0,1,2,"normal","No" 167 | "166",57,1,"asymptomatic",132,207,0,0,168,1,0,1,0,"reversable","No" 168 | "167",52,1,"nonanginal",138,223,0,0,169,0,0,1,NA,"normal","No" 169 | "168",54,0,"nontypical",132,288,1,2,159,1,0,1,1,"normal","No" 170 | "169",35,1,"asymptomatic",126,282,0,2,156,1,0,1,0,"reversable","Yes" 171 | "170",45,0,"nontypical",112,160,0,0,138,0,0,2,0,"normal","No" 172 | "171",70,1,"nonanginal",160,269,0,0,112,1,2.9,2,1,"reversable","Yes" 173 | "172",53,1,"asymptomatic",142,226,0,2,111,1,0,1,0,"reversable","No" 174 | "173",59,0,"asymptomatic",174,249,0,0,143,1,0,2,0,"normal","Yes" 175 | "174",62,0,"asymptomatic",140,394,0,2,157,0,1.2,2,0,"normal","No" 176 | "175",64,1,"asymptomatic",145,212,0,2,132,0,2,2,2,"fixed","Yes" 177 | "176",57,1,"asymptomatic",152,274,0,0,88,1,1.2,2,1,"reversable","Yes" 178 | "177",52,1,"asymptomatic",108,233,1,0,147,0,0.1,1,3,"reversable","No" 179 | "178",56,1,"asymptomatic",132,184,0,2,105,1,2.1,2,1,"fixed","Yes" 180 | "179",43,1,"nonanginal",130,315,0,0,162,0,1.9,1,1,"normal","No" 181 | "180",53,1,"nonanginal",130,246,1,2,173,0,0,1,3,"normal","No" 182 | "181",48,1,"asymptomatic",124,274,0,2,166,0,0.5,2,0,"reversable","Yes" 183 | "182",56,0,"asymptomatic",134,409,0,2,150,1,1.9,2,2,"reversable","Yes" 184 | "183",42,1,"typical",148,244,0,2,178,0,0.8,1,2,"normal","No" 185 | "184",59,1,"typical",178,270,0,2,145,0,4.2,3,0,"reversable","No" 186 | "185",60,0,"asymptomatic",158,305,0,2,161,0,0,1,0,"normal","Yes" 187 | "186",63,0,"nontypical",140,195,0,0,179,0,0,1,2,"normal","No" 188 | "187",42,1,"nonanginal",120,240,1,0,194,0,0.8,3,0,"reversable","No" 189 | "188",66,1,"nontypical",160,246,0,0,120,1,0,2,3,"fixed","Yes" 190 | "189",54,1,"nontypical",192,283,0,2,195,0,0,1,1,"reversable","Yes" 191 | "190",69,1,"nonanginal",140,254,0,2,146,0,2,2,3,"reversable","Yes" 192 | "191",50,1,"nonanginal",129,196,0,0,163,0,0,1,0,"normal","No" 193 | "192",51,1,"asymptomatic",140,298,0,0,122,1,4.2,2,3,"reversable","Yes" 194 | "193",43,1,"asymptomatic",132,247,1,2,143,1,0.1,2,NA,"reversable","Yes" 195 | "194",62,0,"asymptomatic",138,294,1,0,106,0,1.9,2,3,"normal","Yes" 196 | "195",68,0,"nonanginal",120,211,0,2,115,0,1.5,2,0,"normal","No" 197 | "196",67,1,"asymptomatic",100,299,0,2,125,1,0.9,2,2,"normal","Yes" 198 | "197",69,1,"typical",160,234,1,2,131,0,0.1,2,1,"normal","No" 199 | "198",45,0,"asymptomatic",138,236,0,2,152,1,0.2,2,0,"normal","No" 200 | "199",50,0,"nontypical",120,244,0,0,162,0,1.1,1,0,"normal","No" 201 | "200",59,1,"typical",160,273,0,2,125,0,0,1,0,"normal","Yes" 202 | "201",50,0,"asymptomatic",110,254,0,2,159,0,0,1,0,"normal","No" 203 | "202",64,0,"asymptomatic",180,325,0,0,154,1,0,1,0,"normal","No" 204 | "203",57,1,"nonanginal",150,126,1,0,173,0,0.2,1,1,"reversable","No" 205 | "204",64,0,"nonanginal",140,313,0,0,133,0,0.2,1,0,"reversable","No" 206 | "205",43,1,"asymptomatic",110,211,0,0,161,0,0,1,0,"reversable","No" 207 | "206",45,1,"asymptomatic",142,309,0,2,147,1,0,2,3,"reversable","Yes" 208 | "207",58,1,"asymptomatic",128,259,0,2,130,1,3,2,2,"reversable","Yes" 209 | "208",50,1,"asymptomatic",144,200,0,2,126,1,0.9,2,0,"reversable","Yes" 210 | "209",55,1,"nontypical",130,262,0,0,155,0,0,1,0,"normal","No" 211 | "210",62,0,"asymptomatic",150,244,0,0,154,1,1.4,2,0,"normal","Yes" 212 | "211",37,0,"nonanginal",120,215,0,0,170,0,0,1,0,"normal","No" 213 | "212",38,1,"typical",120,231,0,0,182,1,3.8,2,0,"reversable","Yes" 214 | "213",41,1,"nonanginal",130,214,0,2,168,0,2,2,0,"normal","No" 215 | "214",66,0,"asymptomatic",178,228,1,0,165,1,1,2,2,"reversable","Yes" 216 | "215",52,1,"asymptomatic",112,230,0,0,160,0,0,1,1,"normal","Yes" 217 | "216",56,1,"typical",120,193,0,2,162,0,1.9,2,0,"reversable","No" 218 | "217",46,0,"nontypical",105,204,0,0,172,0,0,1,0,"normal","No" 219 | "218",46,0,"asymptomatic",138,243,0,2,152,1,0,2,0,"normal","No" 220 | "219",64,0,"asymptomatic",130,303,0,0,122,0,2,2,2,"normal","No" 221 | "220",59,1,"asymptomatic",138,271,0,2,182,0,0,1,0,"normal","No" 222 | "221",41,0,"nonanginal",112,268,0,2,172,1,0,1,0,"normal","No" 223 | "222",54,0,"nonanginal",108,267,0,2,167,0,0,1,0,"normal","No" 224 | "223",39,0,"nonanginal",94,199,0,0,179,0,0,1,0,"normal","No" 225 | "224",53,1,"asymptomatic",123,282,0,0,95,1,2,2,2,"reversable","Yes" 226 | "225",63,0,"asymptomatic",108,269,0,0,169,1,1.8,2,2,"normal","Yes" 227 | "226",34,0,"nontypical",118,210,0,0,192,0,0.7,1,0,"normal","No" 228 | "227",47,1,"asymptomatic",112,204,0,0,143,0,0.1,1,0,"normal","No" 229 | "228",67,0,"nonanginal",152,277,0,0,172,0,0,1,1,"normal","No" 230 | "229",54,1,"asymptomatic",110,206,0,2,108,1,0,2,1,"normal","Yes" 231 | "230",66,1,"asymptomatic",112,212,0,2,132,1,0.1,1,1,"normal","Yes" 232 | "231",52,0,"nonanginal",136,196,0,2,169,0,0.1,2,0,"normal","No" 233 | "232",55,0,"asymptomatic",180,327,0,1,117,1,3.4,2,0,"normal","Yes" 234 | "233",49,1,"nonanginal",118,149,0,2,126,0,0.8,1,3,"normal","Yes" 235 | "234",74,0,"nontypical",120,269,0,2,121,1,0.2,1,1,"normal","No" 236 | "235",54,0,"nonanginal",160,201,0,0,163,0,0,1,1,"normal","No" 237 | "236",54,1,"asymptomatic",122,286,0,2,116,1,3.2,2,2,"normal","Yes" 238 | "237",56,1,"asymptomatic",130,283,1,2,103,1,1.6,3,0,"reversable","Yes" 239 | "238",46,1,"asymptomatic",120,249,0,2,144,0,0.8,1,0,"reversable","Yes" 240 | "239",49,0,"nontypical",134,271,0,0,162,0,0,2,0,"normal","No" 241 | "240",42,1,"nontypical",120,295,0,0,162,0,0,1,0,"normal","No" 242 | "241",41,1,"nontypical",110,235,0,0,153,0,0,1,0,"normal","No" 243 | "242",41,0,"nontypical",126,306,0,0,163,0,0,1,0,"normal","No" 244 | "243",49,0,"asymptomatic",130,269,0,0,163,0,0,1,0,"normal","No" 245 | "244",61,1,"typical",134,234,0,0,145,0,2.6,2,2,"normal","Yes" 246 | "245",60,0,"nonanginal",120,178,1,0,96,0,0,1,0,"normal","No" 247 | "246",67,1,"asymptomatic",120,237,0,0,71,0,1,2,0,"normal","Yes" 248 | "247",58,1,"asymptomatic",100,234,0,0,156,0,0.1,1,1,"reversable","Yes" 249 | "248",47,1,"asymptomatic",110,275,0,2,118,1,1,2,1,"normal","Yes" 250 | "249",52,1,"asymptomatic",125,212,0,0,168,0,1,1,2,"reversable","Yes" 251 | "250",62,1,"nontypical",128,208,1,2,140,0,0,1,0,"normal","No" 252 | "251",57,1,"asymptomatic",110,201,0,0,126,1,1.5,2,0,"fixed","No" 253 | "252",58,1,"asymptomatic",146,218,0,0,105,0,2,2,1,"reversable","Yes" 254 | "253",64,1,"asymptomatic",128,263,0,0,105,1,0.2,2,1,"reversable","No" 255 | "254",51,0,"nonanginal",120,295,0,2,157,0,0.6,1,0,"normal","No" 256 | "255",43,1,"asymptomatic",115,303,0,0,181,0,1.2,2,0,"normal","No" 257 | "256",42,0,"nonanginal",120,209,0,0,173,0,0,2,0,"normal","No" 258 | "257",67,0,"asymptomatic",106,223,0,0,142,0,0.3,1,2,"normal","No" 259 | "258",76,0,"nonanginal",140,197,0,1,116,0,1.1,2,0,"normal","No" 260 | "259",70,1,"nontypical",156,245,0,2,143,0,0,1,0,"normal","No" 261 | "260",57,1,"nontypical",124,261,0,0,141,0,0.3,1,0,"reversable","Yes" 262 | "261",44,0,"nonanginal",118,242,0,0,149,0,0.3,2,1,"normal","No" 263 | "262",58,0,"nontypical",136,319,1,2,152,0,0,1,2,"normal","Yes" 264 | "263",60,0,"typical",150,240,0,0,171,0,0.9,1,0,"normal","No" 265 | "264",44,1,"nonanginal",120,226,0,0,169,0,0,1,0,"normal","No" 266 | "265",61,1,"asymptomatic",138,166,0,2,125,1,3.6,2,1,"normal","Yes" 267 | "266",42,1,"asymptomatic",136,315,0,0,125,1,1.8,2,0,"fixed","Yes" 268 | "267",52,1,"asymptomatic",128,204,1,0,156,1,1,2,0,NA,"Yes" 269 | "268",59,1,"nonanginal",126,218,1,0,134,0,2.2,2,1,"fixed","Yes" 270 | "269",40,1,"asymptomatic",152,223,0,0,181,0,0,1,0,"reversable","Yes" 271 | "270",42,1,"nonanginal",130,180,0,0,150,0,0,1,0,"normal","No" 272 | "271",61,1,"asymptomatic",140,207,0,2,138,1,1.9,1,1,"reversable","Yes" 273 | "272",66,1,"asymptomatic",160,228,0,2,138,0,2.3,1,0,"fixed","No" 274 | "273",46,1,"asymptomatic",140,311,0,0,120,1,1.8,2,2,"reversable","Yes" 275 | "274",71,0,"asymptomatic",112,149,0,0,125,0,1.6,2,0,"normal","No" 276 | "275",59,1,"typical",134,204,0,0,162,0,0.8,1,2,"normal","Yes" 277 | "276",64,1,"typical",170,227,0,2,155,0,0.6,2,0,"reversable","No" 278 | "277",66,0,"nonanginal",146,278,0,2,152,0,0,2,1,"normal","No" 279 | "278",39,0,"nonanginal",138,220,0,0,152,0,0,2,0,"normal","No" 280 | "279",57,1,"nontypical",154,232,0,2,164,0,0,1,1,"normal","Yes" 281 | "280",58,0,"asymptomatic",130,197,0,0,131,0,0.6,2,0,"normal","No" 282 | "281",57,1,"asymptomatic",110,335,0,0,143,1,3,2,1,"reversable","Yes" 283 | "282",47,1,"nonanginal",130,253,0,0,179,0,0,1,0,"normal","No" 284 | "283",55,0,"asymptomatic",128,205,0,1,130,1,2,2,1,"reversable","Yes" 285 | "284",35,1,"nontypical",122,192,0,0,174,0,0,1,0,"normal","No" 286 | "285",61,1,"asymptomatic",148,203,0,0,161,0,0,1,1,"reversable","Yes" 287 | "286",58,1,"asymptomatic",114,318,0,1,140,0,4.4,3,3,"fixed","Yes" 288 | "287",58,0,"asymptomatic",170,225,1,2,146,1,2.8,2,2,"fixed","Yes" 289 | "288",58,1,"nontypical",125,220,0,0,144,0,0.4,2,NA,"reversable","No" 290 | "289",56,1,"nontypical",130,221,0,2,163,0,0,1,0,"reversable","No" 291 | "290",56,1,"nontypical",120,240,0,0,169,0,0,3,0,"normal","No" 292 | "291",67,1,"nonanginal",152,212,0,2,150,0,0.8,2,0,"reversable","Yes" 293 | "292",55,0,"nontypical",132,342,0,0,166,0,1.2,1,0,"normal","No" 294 | "293",44,1,"asymptomatic",120,169,0,0,144,1,2.8,3,0,"fixed","Yes" 295 | "294",63,1,"asymptomatic",140,187,0,2,144,1,4,1,2,"reversable","Yes" 296 | "295",63,0,"asymptomatic",124,197,0,0,136,1,0,2,0,"normal","Yes" 297 | "296",41,1,"nontypical",120,157,0,0,182,0,0,1,0,"normal","No" 298 | "297",59,1,"asymptomatic",164,176,1,2,90,0,1,2,2,"fixed","Yes" 299 | "298",57,0,"asymptomatic",140,241,0,0,123,1,0.2,2,0,"reversable","Yes" 300 | "299",45,1,"typical",110,264,0,0,132,0,1.2,2,0,"reversable","Yes" 301 | "300",68,1,"asymptomatic",144,193,1,0,141,0,3.4,2,2,"reversable","Yes" 302 | "301",57,1,"asymptomatic",130,131,0,0,115,1,1.2,2,1,"reversable","Yes" 303 | "302",57,0,"nontypical",130,236,0,2,174,0,0,2,1,"normal","Yes" 304 | "303",38,1,"nonanginal",138,175,0,0,173,0,0,1,NA,"normal","No" 305 | -------------------------------------------------------------------------------- /Data/Income1.csv: -------------------------------------------------------------------------------- 1 | "","Education","Income" 2 | "1",10,26.6588387834389 3 | "2",10.4013377926421,27.3064353457772 4 | "3",10.8428093645485,22.1324101716143 5 | "4",11.2441471571906,21.1698405046065 6 | "5",11.6454849498328,15.1926335164307 7 | "6",12.0869565217391,26.3989510407284 8 | "7",12.4882943143813,17.435306578572 9 | "8",12.8896321070234,25.5078852305278 10 | "9",13.2909698996656,36.884594694235 11 | "10",13.7324414715719,39.666108747637 12 | "11",14.133779264214,34.3962805641312 13 | "12",14.5351170568562,41.4979935356871 14 | "13",14.9765886287625,44.9815748660704 15 | "14",15.3779264214047,47.039595257834 16 | "15",15.7792642140468,48.2525782901863 17 | "16",16.2207357859532,57.0342513373801 18 | "17",16.6220735785953,51.4909192102538 19 | "18",17.0234113712375,61.3366205527288 20 | "19",17.4648829431438,57.581988179306 21 | "20",17.866220735786,68.5537140185881 22 | "21",18.2675585284281,64.310925303692 23 | "22",18.7090301003344,68.9590086393083 24 | "23",19.1103678929766,74.6146392793647 25 | "24",19.5117056856187,71.8671953042483 26 | "25",19.9130434782609,76.098135379724 27 | "26",20.3545150501672,75.77521802986 28 | "27",20.7558528428094,72.4860553152424 29 | "28",21.1571906354515,77.3550205741877 30 | "29",21.5986622073579,72.1187904524136 31 | "30",22,80.2605705009016 32 | -------------------------------------------------------------------------------- /Data/Income2.csv: -------------------------------------------------------------------------------- 1 | "","Education","Seniority","Income" 2 | "1",21.5862068965517,113.103448275862,99.9171726114381 3 | "2",18.2758620689655,119.310344827586,92.579134855529 4 | "3",12.0689655172414,100.689655172414,34.6787271520874 5 | "4",17.0344827586207,187.586206896552,78.7028062353695 6 | "5",19.9310344827586,20,68.0099216471551 7 | "6",18.2758620689655,26.2068965517241,71.5044853814318 8 | "7",19.9310344827586,150.344827586207,87.9704669939115 9 | "8",21.1724137931034,82.0689655172414,79.8110298331255 10 | "9",20.3448275862069,88.2758620689655,90.00632710858 11 | "10",10,113.103448275862,45.6555294997364 12 | "11",13.7241379310345,51.0344827586207,31.9138079371295 13 | "12",18.6896551724138,144.137931034483,96.2829968022869 14 | "13",11.6551724137931,20,27.9825049000603 15 | "14",16.6206896551724,94.4827586206897,66.601792415137 16 | "15",10,187.586206896552,41.5319924201478 17 | "16",20.3448275862069,94.4827586206897,89.00070081522 18 | "17",14.1379310344828,20,28.8163007592387 19 | "18",16.6206896551724,44.8275862068966,57.6816942573605 20 | "19",16.6206896551724,175.172413793103,70.1050960424457 21 | "20",20.3448275862069,187.586206896552,98.8340115435447 22 | "21",18.2758620689655,100.689655172414,74.7046991976891 23 | "22",14.551724137931,137.931034482759,53.5321056283034 24 | "23",17.448275862069,94.4827586206897,72.0789236655191 25 | "24",10.4137931034483,32.4137931034483,18.5706650327685 26 | "25",21.5862068965517,20,78.8057842852386 27 | "26",11.2413793103448,44.8275862068966,21.388561306174 28 | "27",19.9310344827586,168.965517241379,90.8140351180409 29 | "28",11.6551724137931,57.2413793103448,22.6361626208955 30 | "29",12.0689655172414,32.4137931034483,17.613593041445 31 | "30",17.0344827586207,106.896551724138,74.6109601985289 32 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | ## Приложения к книге "Введение в статистическое обучение с примерами на языке R" 2 | 3 | Этот репозиторий содержит файлы скриптов на языке R и наборы данных, необходимые для выполнение лабораторных работ из книги [_"Джеймс Г., Уиттон Д., Хасти Т., Тибширани Р. Введение в статистическое обучение с примерами на языке R. Пер. с англ. С. Э. Мастицкого - М.: ДМК Пресс, 2016. – 449 с.: ил."_](http://dmkpress.com/catalog/computer/statistics/978-5-97060-293-5/) (оригинальное название [_"An Introduction to Statistical Learning with Applications in R"_](http://www-bcf.usc.edu/~gareth/ISL/index.html)). 4 | 5 | Репозиторий разбит на две директории: 6 | 7 | * `Code`: примеры кода для каждой главы 8 | * `Data`: соответствующие наборы данных 9 | 10 | В файле `sample.pdf` можно ознакомиться с оглавлением и отрывками из первых двух глав книги. 11 | 12 | С вопросами и предложениями по поводу содержания этого репозитория обращайтесь, пожалуйста, по [электронной почте](mailto:rtutorialsbook@gmail.com). 13 | 14 | ## Ошибки, обнаруженные в первом издании книги (список обновлен 15 декабря 2016 г.) 15 | 16 | К сожалению, после публикации первого издания (апрель 2016 г.) в книге был найден ряд опечаток и ошибок технического характера (огромное спасибо всем читателям, которые сообщили о них!). С их списком можно ознакомиться ниже. Все эти неточности и ошибки будут учтены в последующих изданиях. 17 | 18 | * **Опечатки в матрице, представленной вверху на стр. 23**: эта матрица должна выглядеть следующим образом: ![](https://dl.dropboxusercontent.com/u/7521662/rtutorials/islr-ru-files/matrix_p_23.PNG) 19 | 20 | * **Лишнее слово в начале 2-го абзаца на стр. 28**: вместо "...на образование (years of education; ..." должно быть "на образование (years; ..." 21 | 22 | * **Лишнее слово в начале 2-го абзаца на стр. 27**: вместо "...тогда как sales - это выходной переменной..." должно быть "тогда как sales - выходной переменной" 23 | 24 | * **Пропущено слово в конце 3-го абзаца на стр. 30**: вместо "...в зависимости условий производства..." должно быть "...в зависимости от условий производства" 25 | 26 | * **Опечатка в первом абзаце на стр. 41**: должно быть "...(т.е. переменной с двумя..." 27 | 28 | * **Стр. 44-46, рисунки 2.9-2.11 (справа)**: перепутаны подписи осей. Ось X должна быть подписана как "Гибкость", а ось Y - как "Среднеквадратичная ошибка" 29 | 30 | * **Опечатка в 1-м абзаце на стр. 58**: должно быть "...при вызове этой функции...", а не "...при вызове этой функций..." 31 | 32 | * **Опечатка во 2-м абзаце на стр. 58**: должно быть "...воспроизводил один и тот же набор...", а не "...воспроизводил один тот же набор..." 33 | 34 | * **Стр. 58**: Вместо sd() на поля второй раз ошибочно вынесено mean() 35 | 36 | * **Опечатка в последнем предложении на стр. 59**: должно быть "...значений y...", а не "...значения y..." 37 | 38 | * **Опечатка в конце 2-го абзаца на стр. 60**: вместо "?controur" должно быть "?contour" 39 | 40 | * **Опечатка в 4-м абзаце на стр. 62**: вместо "read.table()" должно быть "read.csv()" 41 | 42 | * **Лишнее слово во 2-м абзаце на стр. 65**: вместо "...у нас есть имеется..." должно быть "...у нас имеется..." 43 | 44 | * **Опечатка в пункте 9(а) на стр. 69**: вместо "Какие предикторы явлются..." должно быть "Какие предикторы являются..." 45 | 46 | * **Стр. 79, 4-я строка сверху, пропущено слово**: вместо "...95-ный доверительный для..." должно быть "...95-ный доверительный интервал для..." 47 | 48 | * **Стр. 79, после уравнения (3.13)**: вместо "...против $H_0:$ ..." должно быть "...против $H_a:$ ..." 49 | 50 | * **Опечатка на стр. 84, после уравнения (3.19)**: вместо "$b_j$" дожно быть "$beta_j$" 51 | 52 | * **Опечатки на стр. 92, 3-й абзац сверху**: 1) вместо "...при добавлении newspapers в модель..." должно быть "...при добавлении newspaper в модель..."; 2) вместо "...p–значение для radio было незначимым." должно быть "p–значение для newspaper было незначимым." 53 | 54 | * **Стр. 92, последний абзац**: первое предложение в этом абзаце должно выглядеть следующим образом: "RSE у модели, содержащей в качестве предикторов только TV и radio, составляет 1.681, а у модели, которая включает также newspaper, RSE = 1.686 (табл. 3.6)." 55 | 56 | * **Стр. 99**: заголовок "Расширения линейной модели" должен быть заголовком подраздела, "3.3.2 Расширения линейной модели" 57 | 58 | * **Стр. 100, уравнение (3.32)**: член "beta_3 X_1 X_2" после первого знака "=" лишний. 59 | 60 | * **Стр. 102, уравнение (3.34)**: это уравнение должно выглядеть следующим образом: 61 | 62 | ![Уравнение 3.34](https://dl.dropboxusercontent.com/u/7521662/rtutorials/islr-ru-files/eq_3_34.PNG) 63 | 64 | * **Стр. 105, неверная нумерация подраздела**: вместо "3.3.1 Потенциальные проблемы" должно быть "3.3.3 Потенциальные проблемы" 65 | 66 | * **Стр. 110, последний абзац**: слово "этого" в последнем предложении лишнее. 67 | 68 | * **Стр. 111, рисунок 3.11 (справа)**: опечатка в подписи оси Х. Вместо "Показтель" должно быть "Показатель" 69 | 70 | * **Опечатка на стр. 112, 4-я строка снизу**: вместо "...этом рисунке..." должно быть "...на этом рисунке..." 71 | 72 | * **Опечатка на стр. 114, 2-й абзац снизу**: вместо "...для каждого предиктора рассчитывает путем..." должно быть "...для каждого предиктора рассчитывается путем..." 73 | 74 | * **Стр. 115, таблица 3.11**: эта таблица должна выглядеть следующим образом: 75 | 76 | ![Таблица 3.11](https://dl.dropboxusercontent.com/u/7521662/rtutorials/islr-ru-files/table_3_11.PNG) 77 | 78 | * **Опечатка на стр. 116, 12-я строка сверху**: должно быть "минимально" вместо "минимиально" 79 | 80 | * **Опечатка на стр. 117, 2-я строка сверху**: должно быть "реклама на телевидении" вместо "реклама не телевидении" 81 | 82 | * **Опечатка на стр. 117, 2-й абзац**: вместо "...с количеством продажам." должно быть "...с количеством продаж." 83 | 84 | * **Стр. 122, подпись к рис. 3.19**: эта подпись ошибочно была скопирована с подписи к рис. 3.18. Правильная подпись должна выглядеть следующим образом: 85 | 86 | "Слева вверху: Приведены KNN–модели с K = 1 (голубая кривая) и K = 9 (красная кривая) для случая со слабой нелинейной зависимостью между X и Y (черная сплошная кривая). Справа вверху: Показаны MSE на контрольной выборке для линейной регрессии по методу наименьших квадратов (горизонтальная черная линия) и для KNN–моделей с разными значениями 1/K (зеленая кривая), подогнанных к данным со слабой нелинейной зависимостью. Слева и справа внизу: То же, что и вверху, но для случая с выраженной нелинейной зависимостью между X и Y" 87 | 88 | * **Стр. 127, перед последним блоком кода**: вместо "rstudent()" на поле страницы должно быть вынесено "hatvalues()" 89 | 90 | * **Стр. 131, абзац после первого блока с кодом**: продублирована следующая часть текста: "Здесь модель M1 ... зависимости между medv и lstat." Как следствие, продублировано и примечание к этому тексту и нарушена нумерация всех последующих примечаний в предалах главы 3 91 | 92 | * **Ошибки на стр. 135, пункт 3**: вместо "Независимой переменной является начальная заработная плата после окончания университете..." должно быть "Зависимой переменной является начальная заработная плата после окончания университета..." 93 | 94 | * **Опечатка на стр. 137, пункт 8, подпункт (а) iii**: вместо "Каково направление связь..." должно быть "Каково направление связи..." 95 | 96 | * **Стр. 138, пункт 10, подпункт (e)**: слово "было" продублировано 97 | 98 | * **Стр. 143, опечатки в первых двух предложениях 1-го абзаца**: должно быть "...зависимая переменная Y является..." и "...часто зависимая переменная является...". На той же странице, 2-й абзац: должно быть "...три наиболее широко распространенных классификатора: *логистическую регрессиию*..." 99 | 100 | * **Стр. 146, 5-й абзац сверху**: должно быть "...нелегко приспособить для качественных откликов" и "...предназначены для качественных откликов." 101 | 102 | * **Опечатка на стр. 148, 3-й абзац сверху**: вместо "Для подгонки модели (4.1)..." должно быть "Для подгонки модели (4.2)..." 103 | 104 | * **Стр. 152, 5-я строка снизу**: слово "предложить" продублировано 105 | 106 | * **Стр. 154, в конце первого абзаца**: должно быть "...такой подход возможен и программное обеспечение..." 107 | 108 | * **Стр. 156, опечатка в начале 3-го раздела**: вместо "(Заметьте, что $\pi_k$ в (4.14)..." должно быть "(Заметьте, что $\pi_k$ в (4.12)" 109 | 110 | * **Стр. 156, опечатка в уравнении (4.14)**: "мю" в знаменателе после первого знака "равно" не должны возводиться в квадрат 111 | 112 | * **Стр. 156, опечатка в конце 3-го абзаца сверху**: вместо "...Таким образом, что LDA хорошо..." должно быть "Таким образом, LDA хорошо..." 113 | 114 | * **Стр. 170, пропущено слово в середине 2-го абзаца сверху**: вместо "...тогда существенно более гибкий..." должно быть "...тогда как существенно более гибкий..." 115 | 116 | * **Стр. 176, опечатка в 1-м абзаце**: вместо "...предсказанных случая" должно быть "...предсказанных случаев" 117 | 118 | * **Стр. 176, опечатка во 2-м абзаце (6-я строка)**: вместо "...частоты ошибок на обучающих..." должно быть "...частота ошибок на обучающих..." 119 | 120 | * **Стр. 177. 1-й листинг**: строки с 4-й по 6-ю должны идти после последней строки во 2-м листинге на той же странице 121 | 122 | * **Стр. 191, опечатка в пункте d**: вместо "...в объекте по названием..." должно быть "...в объекте под названием..." 123 | 124 | * **Опечатка на стр. 198 в термине, вынесенном на поле страницы**: должно быть "k-кратная" вместо "k-крантная" 125 | 126 | * **Стр. 212, 2-й абзац, пропущено слово**: вместо "...в пользу того, полиномы..." должно быть вместо "...в пользу того, что полиномы..." 127 | 128 | * **Опечатки на стр. 214, предпоследний абзац**: вместо "К обсуждалось в подразделе 3.2.1..." должно быть "Как обсуждалось в подразделе 3.1.2..." 129 | 130 | * **Опечатка в 1-м абзаце на стр. 224**: вместо "...но прим этом..." должно быть "...но при этом..." 131 | 132 | * **Опечатка на стр. 231, первый абзац**: должно быть "...пропорциональны друг другу..." вместо "...пропорциональных друг другу..." 133 | 134 | * **Опечатка на стр. 237, середина первого абзаца**: должно быть "...приводит к существенному..." вместо "...приводит в существенному..." 135 | 136 | * **Стр. 239, формула 6.7**: у второй и третьей суммы в качестве индекса указано i, а должно быть j 137 | 138 | * **Стр. 240, 1-й абзац**: неверный порядок перечисления моделей: должно быть "...коэффициентов лассо-модели и гребневой регрессии..." 139 | 140 | * **Опечатка на стр. 241, 4-й абзац**: вместо "...раны нулю?" должно быть "...равны нулю?" 141 | 142 | * **Опечатка на стр. 252 в уравнении (6.19)**: коэффициент при первом слагаемом должен быть 0.839, а не 0.893 143 | 144 | * **После 2-го абзаца на стр. 252 пропущен следующий небольшой абзац:** 145 | 146 | ![](https://dl.dropboxusercontent.com/u/7521662/rtutorials/islr-ru-files/missing_part_p_254.PNG) 147 | 148 | * **Стр. 256**: продублировано слово в "Это связано с тем, что что..." 149 | 150 | * **Стр. 260, опечатка в последнем предложении пункта 2**: вместо "...намного превышает этого значение" должно быть "намного превышает это значение" 151 | 152 | * **Стр. 263, опечатка в первом абзаце**: вместо "Рисунок 24..." должно быть "Рисунок 6.24..." 153 | 154 | * **Стр. 264, опечатка в конце первого абзаца**: вместо "...качественными предсказательным моделям..." должно быть "...качественным предсказательным моделям..." 155 | 156 | * **Первый листинг кода на стр. 266**: элементы `{` и `> mean(store)` не нужны 157 | 158 | * **Опечатки на стр. 266, 2-й абзац**: в тексте и на полях вместо `regsubset()` должно быть `regsubsets()` 159 | 160 | * **Опечатка на стр. 270, 1-й абзац**: вместо `regsubset()` должно быть `regsubsets()` 161 | 162 | * **Опечатка на стр. 274, 1-я строка 2-го листинга**: вместо ` ridge.mod$lambda[60]` должно быть ` ridge.mod$lambda[50]` 163 | 164 | * **Опечатка на стр. 276, в конце 2-го абзаца**: вместо "...зернj генератора..." должно быть "...зерно генератора..." 165 | 166 | * **Опечатка на стр. 278, 1-й абзац**: вместо "...библиотеки pls()." должно быть "...библиотеки pls." 167 | 168 | * **Опечатка на стр. 280, 1-й абзац**: вместо "...библиотеки pls()." должно быть "...библиотеки pls." 169 | 170 | * **Пропущено слово на стр. 288, в конце 1-го абзаца**: вместо "...более сложные подходы, такие сплайны..." должно быть "...более сложные подходы, такие как сплайны..." 171 | 172 | * **Опечатка на стр. 289, уравнение (7.1)**: пропущен знак `+` перед эпсилон 173 | 174 | * **Опечатка на стр. 291 в термине, вынесенном на поля**: вместо "катетегориальная" должно быть "категориальная" 175 | 176 | * **Опечатка в сноске на стр. 292**: вместо "...перечисленных в (5.7)..." должно быть "...перечисленных в (7.5)..." 177 | 178 | * **Опечатка на стр. 302**: вместо "...через всех обучающие..." должно быть "...через все обучающие..." 179 | 180 | * **Опечатка на стр. 305, пункт 3 Алгоритма 7.1**: вместо "...нахождения $\hat{\beta}_1$ и $\hat{\beta}_2$..." должно быть "...нахождения $\hat{\beta}_0$ и $\hat{\beta}_1$..." 181 | 182 | * **Опечатка в формуле (7.15) на стр. 308**: в первой строке этого уравнения должно быть $f_j$, а не $f_i$. Кроме того, во второй строке вместо $f_1(x_{ij})$ должно быть $f_1(x_{i1})$ 183 | 184 | * **Опечатки во 2-м абзаце на стр. 308**: и у f, и у X индекс должен обозначаться буквой j, а не i 185 | 186 | * **Стр. 308, 3-й абзац**: пропущен один из уровней переменной `education`, т.е. должно быть "...переменной с пятью уровнями - Coll..." 187 | 188 | * **Стр. 312, опечатка в подписи к рис. 7.13**: вместо "...из таблицы I(Wage)." должно быть "...из таблицы Wage." 189 | 190 | * **Стр. 313, опечатка в термине, вынесенном на поля**: вместо "отогональные полиномы" должно быть "ортогональные полиномы" 191 | 192 | * **Стр. 319, опечатка во предпоследнем абзаце**: вместо "...ширины окна 0.1 и 0.5..." должно быть "...ширины окна 0.2 и 0.5..." 193 | 194 | * **Стр. 321, опечатка во 1-м абзаце**: вместо "...которая не вообще не содержит..." должно быть "...которая вообще не содержит..." 195 | 196 | * **Стр. 322, продублировано слово во 2-м абзаце**: вместо "При построении построении..." должно быть "При построении..." 197 | 198 | * **Стр. 323, строки 3, 7 и 11**: при перечислении коэффицентов модели пропущен $\beta_3$. 199 | 200 | * **Стр. 332, опечатка во 3-м абзаце**: вместо "...быстро, особенное когда количество..." должно быть "...быстро, особенно когда количество..." 201 | 202 | * **Стр. 351, опечатка в последнем абзаце**: вместо "В этом наборе данных Seats..." должно быть "В этом наборе данных Sales..." 203 | 204 | * **Стр. 355, опечатка в последнем абзаце**: вместо "rm > 7.437" должно быть "rm >= 7.437" 205 | 206 | * **Стр. 359, опечатка во 2-м абзаце**: вместо "...по контрольной данным:" должно быть "...по контрольным данным:" 207 | 208 | * **Стр. 366, опечатка во 2-м абзаце**: вместо "...показаны на слева рис. 9.2." должно быть "...показаны на слева на рис. 9.2." 209 | 210 | * **Стр. 367, последний абзац**: в формуле для $f(x*)$ пропущен коэффициент $\beta_0$ 211 | 212 | * **Стр. 371, опечатка в названии раздела**: должно быть "...на опорных векторах" 213 | 214 | * **Стр. 374, формула (9.15)**: между знаком суммы и знаком "меньше либо равно" не хватает $\epsilon_i$ 215 | 216 | * **Стр. 375, 4-я строка сверху**: между знаком суммы и знаком "меньше либо равно" не хватает $\epsilon_i$ 217 | 218 | * **Стр. 378, последняя строка уравнения (9.16)**: у первого знака суммы индексирование должно выполняться по i, а не j 219 | 220 | * **Стр. 383, опечатка в 1-м абзаце**: вместо "...статистически значимыми" должно быть "... статистически значимым" 221 | 222 | * **Стр. 385, 1-й абзац**: продублировано слово в "...связи между между SVM..." 223 | 224 | * **Стр. 386, опечатка во 2-м абзаце**: вместо "...на логистическую регрессии..." должно быть "...на логистическую регрессию..." 225 | 226 | * **Стр. 401, опечатка в 1-м абзаце**: вместо "...?plot.smv" должно быть "...?plot.svm" 227 | 228 | * **Стр. 404. 5-й абзац, "...в виду то обстоятельство, что формула..."**: в этой формуле знак = перед фи не нужен 229 | 230 | * **Стр. 405. 2-й абзац**: знак = между занком суммы и фи не нужен 231 | 232 | * **Стр. 406. ошибка в последнем абзаце**: вместо "...и очень низкий вес переменной Assault" должно быть "...и очень низкий вес переменной UrbanPop" 233 | 234 | * **Стр. 408, опечатки в 4-м абзаце**: вместо "...максимальной близко к n наблюдениям" должно быть "...расположенную максимально близко к n наблюдениям" 235 | 236 | * **Стр. 408, формула (10.5)**: эта формула должна выглядеть следующим образом: 237 | 238 | ![](https://dl.dropboxusercontent.com/u/7521662/rtutorials/islr-ru-files/eq_10_5.PNG) 239 | 240 | * **Стр. 409, опечатка в подписи к рис. 10.2**: вместо "...до плоскости мнимальна" должно быть "...до плоскости минимальна" 241 | 242 | * **Стр. 410, первая строка**: должно быть "UrbanPop", а не "UrbabPop" 243 | 244 | * **Стр. 426, опечатка в последнем абзаце**: вместо "До сих в примерах..." должно быть "До сих пор в примерах..." 245 | 246 | * **Стр. 427, опечатка в первом абзаце**: вместо "...она рассчитываться..." должно быть "...она рассчитывается..." 247 | 248 | * **Стр. 429, 1-й абзац**: в "...чтобы их стандартные стали равны 1" пропущено слово "отклонения" 249 | 250 | * **Стр. 433, опечатка в 4-м абзаце**: вместо "Используя функцию prcom()..." должно быть "Используя функцию prcomp()..." 251 | 252 | * **Стр. 437, 1-й абзац"**: следует читать "Не менее легко мы могли бы выполнить иерархическую кластеризацию на основе среднего или одиночного присоединения:" 253 | 254 | * **Стр. 437, 3-й листинг, 1-я строка**: эта строка не нужна 255 | 256 | * **Опечатка на стр. 440, последний абзац**: вместо "...а элементы cumsum(pre)..." должно быть "...а элементы cumsum(pve)..." 257 | 258 | * **Стр. 442, рис. 10.17, перепутаны заголовки графиков**: Сначала должно идти "Полное присоединение", а затем - "Среднее присоединение". Соответственно, в подписи к этому рисунку должно быть "...на основе полного, среднего и одиночного типов..." 259 | -------------------------------------------------------------------------------- /sample.pdf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/ranalytics/islr-ru/890bad56b470c1f91ec823977d1b0b151f4733f8/sample.pdf --------------------------------------------------------------------------------