├── classification ├── naivebayes │ ├── data │ │ ├── test │ │ │ └── posting.txt │ │ ├── training │ │ │ ├── C0_posting_1.txt │ │ │ ├── C1_posting_3.txt │ │ │ ├── C1_posting_4.txt │ │ │ ├── C0_posting_0.txt │ │ │ └── C1_posting_2.txt │ │ └── .directory │ ├── .directory │ ├── test │ │ ├── .directory │ │ └── OfflineNBCTester.cpp │ ├── Vector.h │ ├── FileTokenizer.h │ ├── InputDataSet.h │ ├── makefile │ └── FileTokenizer.cpp ├── adaboost │ ├── data │ │ ├── points.txt │ │ └── .directory │ ├── .directory │ ├── WeakClassifier.cpp │ ├── WeakClassifier.h │ ├── AdaptiveBoost.h │ ├── WeakLearner.h │ └── makefile ├── knn │ ├── .directory │ ├── trainingDigits │ │ └── .directory │ ├── makefile │ ├── NMinHeap.h │ ├── test │ │ ├── NMinHeapTester.cpp │ │ ├── InputDataSetTester.cpp │ │ └── KNearestNeighboursTester.cpp │ ├── InputDataSet.h │ ├── KNearestNeighbours.h │ └── testDigits │ │ ├── 0_0.txt │ │ ├── 0_1.txt │ │ ├── 0_10.txt │ │ ├── 0_11.txt │ │ ├── 0_12.txt │ │ ├── 0_13.txt │ │ ├── 0_14.txt │ │ ├── 0_15.txt │ │ ├── 0_16.txt │ │ ├── 0_17.txt │ │ ├── 0_18.txt │ │ ├── 0_19.txt │ │ ├── 0_2.txt │ │ ├── 0_20.txt │ │ ├── 0_21.txt │ │ ├── 0_22.txt │ │ ├── 0_23.txt │ │ ├── 0_24.txt │ │ ├── 0_25.txt │ │ ├── 0_26.txt │ │ ├── 0_27.txt │ │ ├── 0_28.txt │ │ ├── 0_29.txt │ │ ├── 0_3.txt │ │ ├── 0_30.txt │ │ ├── 0_31.txt │ │ ├── 0_32.txt │ │ ├── 0_33.txt │ │ ├── 0_34.txt │ │ ├── 0_35.txt │ │ ├── 0_36.txt │ │ ├── 0_37.txt │ │ ├── 0_38.txt │ │ ├── 0_39.txt │ │ ├── 0_4.txt │ │ ├── 0_40.txt │ │ ├── 0_41.txt │ │ ├── 0_42.txt │ │ ├── 0_43.txt │ │ ├── 0_44.txt │ │ ├── 0_45.txt │ │ ├── 0_46.txt │ │ ├── 0_47.txt │ │ ├── 0_48.txt │ │ ├── 0_49.txt │ │ ├── 0_5.txt │ │ ├── 0_50.txt │ │ ├── 0_51.txt │ │ ├── 0_52.txt │ │ ├── 0_53.txt │ │ ├── 0_54.txt │ │ ├── 0_55.txt │ │ ├── 0_56.txt │ │ ├── 0_57.txt │ │ ├── 0_58.txt │ │ ├── 0_59.txt │ │ ├── 0_6.txt │ │ ├── 0_60.txt │ │ ├── 0_61.txt │ │ ├── 0_62.txt │ │ ├── 0_63.txt │ │ ├── 0_64.txt │ │ ├── 0_65.txt │ │ ├── 0_66.txt │ │ ├── 0_67.txt │ │ ├── 0_68.txt │ │ ├── 0_69.txt │ │ ├── 0_7.txt │ │ ├── 0_70.txt │ │ ├── 0_71.txt │ │ ├── 0_72.txt │ │ ├── 0_73.txt │ │ ├── 0_74.txt │ │ ├── 0_75.txt │ │ ├── 0_76.txt │ │ ├── 0_77.txt │ │ ├── 0_78.txt │ │ ├── 0_79.txt │ │ ├── 0_8.txt │ │ ├── 0_80.txt │ │ ├── 0_81.txt │ │ ├── 0_82.txt │ │ ├── 0_83.txt │ │ ├── 0_84.txt │ │ ├── 0_85.txt │ │ ├── 0_86.txt │ │ ├── 0_9.txt │ │ ├── 1_0.txt │ │ ├── 1_1.txt │ │ ├── 1_10.txt │ │ ├── 1_11.txt │ │ ├── 1_12.txt │ │ ├── 1_13.txt │ │ ├── 1_14.txt │ │ ├── 1_15.txt │ │ ├── 1_16.txt │ │ ├── 1_17.txt │ │ ├── 1_18.txt │ │ ├── 1_19.txt │ │ ├── 1_2.txt │ │ ├── 1_20.txt │ │ ├── 1_21.txt │ │ ├── 1_22.txt │ │ ├── 1_23.txt │ │ ├── 1_24.txt │ │ ├── 1_25.txt │ │ ├── 1_26.txt │ │ ├── 1_27.txt │ │ ├── 1_28.txt │ │ ├── 1_29.txt │ │ ├── 1_3.txt │ │ ├── 1_30.txt │ │ ├── 1_31.txt │ │ ├── 1_32.txt │ │ ├── 1_33.txt │ │ ├── 1_34.txt │ │ ├── 1_35.txt │ │ ├── 1_36.txt │ │ ├── 1_37.txt │ │ ├── 1_38.txt │ │ ├── 1_39.txt │ │ ├── 1_4.txt │ │ ├── 1_40.txt │ │ ├── 1_41.txt │ │ ├── 1_42.txt │ │ ├── 1_43.txt │ │ ├── 1_44.txt │ │ ├── 1_45.txt │ │ ├── 1_46.txt │ │ ├── 1_47.txt │ │ ├── 1_48.txt │ │ ├── 1_49.txt │ │ ├── 1_5.txt │ │ ├── 1_50.txt │ │ ├── 1_51.txt │ │ ├── 1_52.txt │ │ ├── 1_53.txt │ │ ├── 1_54.txt │ │ ├── 1_55.txt │ │ └── 1_56.txt ├── decisiontree │ ├── .directory │ ├── data │ │ ├── species.txt │ │ └── lenses.data │ ├── test │ │ └── DecisionTreeTester.cpp │ └── makefile └── regission │ ├── .directory │ ├── data │ └── .directory │ ├── test │ ├── .directory │ └── LogisticRegressionTester.cpp │ ├── RegressionFunction.h │ ├── Sigmoid.h │ ├── Sigmoid.cpp │ ├── LogisticRegression.h │ └── makefile ├── clustering ├── kmeans │ ├── data │ │ └── points.txt │ ├── .directory │ ├── test │ │ └── OfflineKMeansTester.cpp │ ├── makefile │ └── OfflineKMeans.h └── apriori │ ├── makefile │ └── test │ └── AprioriTester.cpp ├── common ├── .directory ├── StringDataReader.cpp ├── DataReader.h ├── FloatDataReader.h ├── StringDataReader.h ├── IndexOutOfBound.h └── IndexOutOfBound.cpp ├── utility ├── Timing.h ├── Utils.cpp └── Utils.h └── README /classification/naivebayes/data/test/posting.txt: -------------------------------------------------------------------------------- 1 | four two three six 2 | -------------------------------------------------------------------------------- /classification/naivebayes/data/training/C0_posting_1.txt: -------------------------------------------------------------------------------- 1 | three one two 2 | -------------------------------------------------------------------------------- /classification/naivebayes/data/training/C1_posting_3.txt: -------------------------------------------------------------------------------- 1 | two five four 2 | -------------------------------------------------------------------------------- /classification/naivebayes/data/training/C1_posting_4.txt: -------------------------------------------------------------------------------- 1 | eight ten nine 2 | -------------------------------------------------------------------------------- /classification/naivebayes/data/training/C0_posting_0.txt: -------------------------------------------------------------------------------- 1 | five four three two 2 | -------------------------------------------------------------------------------- /classification/naivebayes/data/training/C1_posting_2.txt: -------------------------------------------------------------------------------- 1 | six seven ten eight 2 | -------------------------------------------------------------------------------- /classification/adaboost/data/points.txt: -------------------------------------------------------------------------------- 1 | X Y Class 2 | 1.0 2.1 1.0 3 | 2.0 1.1 1.0 4 | 1.3 1.0 -1.0 5 | 1.0 1.0 -1.0 6 | 2.0 1.0 1.0 7 | -------------------------------------------------------------------------------- /clustering/kmeans/data/points.txt: -------------------------------------------------------------------------------- 1 | X Y Class 2 | 1.6 3.6 0 3 | -2.4 3.4 0 4 | -1.3 -3.3 0 5 | 0.9 2.9 0 6 | -3.5 1.5 0 7 | -3.4 -1.7 0 8 | -------------------------------------------------------------------------------- /common/.directory: -------------------------------------------------------------------------------- 1 | [Dolphin] 2 | AdditionalInfoV2=Details_Size,Details_Date,CustomizedDetails 3 | Timestamp=2013,1,6,16,58,30 4 | Version=2 5 | ViewMode=1 6 | -------------------------------------------------------------------------------- /clustering/kmeans/.directory: -------------------------------------------------------------------------------- 1 | [Dolphin] 2 | AdditionalInfoV2=Details_Size,Details_Date,CustomizedDetails 3 | Timestamp=2013,1,11,0,17,18 4 | Version=2 5 | ViewMode=1 6 | -------------------------------------------------------------------------------- /classification/knn/.directory: -------------------------------------------------------------------------------- 1 | [Dolphin] 2 | AdditionalInfoV2=Details_Size,Details_Date,CustomizedDetails 3 | Timestamp=2013,1,6,16,52,42 4 | Version=2 5 | ViewMode=1 6 | -------------------------------------------------------------------------------- /classification/adaboost/.directory: -------------------------------------------------------------------------------- 1 | [Dolphin] 2 | AdditionalInfoV2=Details_Size,Details_Date,CustomizedDetails 3 | Timestamp=2013,1,10,15,51,39 4 | Version=2 5 | ViewMode=1 6 | -------------------------------------------------------------------------------- /classification/decisiontree/.directory: -------------------------------------------------------------------------------- 1 | [Dolphin] 2 | AdditionalInfoV2=Details_Size,Details_Date,CustomizedDetails 3 | Timestamp=2012,12,31,0,7,37 4 | Version=2 5 | ViewMode=1 6 | -------------------------------------------------------------------------------- /classification/naivebayes/.directory: -------------------------------------------------------------------------------- 1 | [Dolphin] 2 | AdditionalInfoV2=Details_Size,Details_Date,CustomizedDetails 3 | Timestamp=2013,1,3,12,54,9 4 | Version=2 5 | ViewMode=1 6 | -------------------------------------------------------------------------------- /classification/regission/.directory: -------------------------------------------------------------------------------- 1 | [Dolphin] 2 | AdditionalInfoV2=Details_Size,Details_Date,CustomizedDetails 3 | Timestamp=2013,1,5,16,21,22 4 | Version=2 5 | ViewMode=1 6 | -------------------------------------------------------------------------------- /utility/Timing.h: -------------------------------------------------------------------------------- 1 | #ifndef _TIMING_H_ 2 | #define _TIMING_H_ 3 | 4 | typedef long long int64; 5 | typedef unsigned long long uint64; 6 | int64 getTimeMs64(); 7 | 8 | #endif 9 | -------------------------------------------------------------------------------- /classification/adaboost/data/.directory: -------------------------------------------------------------------------------- 1 | [Dolphin] 2 | AdditionalInfoV2=Details_Size,Details_Date,CustomizedDetails 3 | Timestamp=2013,1,5,14,31,35 4 | Version=2 5 | ViewMode=1 6 | -------------------------------------------------------------------------------- /classification/naivebayes/data/.directory: -------------------------------------------------------------------------------- 1 | [Dolphin] 2 | AdditionalInfoV2=Details_Size,Details_Date,CustomizedDetails 3 | Timestamp=2013,1,4,13,17,54 4 | Version=2 5 | ViewMode=1 6 | -------------------------------------------------------------------------------- /classification/naivebayes/test/.directory: -------------------------------------------------------------------------------- 1 | [Dolphin] 2 | AdditionalInfoV2=Details_Size,Details_Date,CustomizedDetails 3 | Timestamp=2013,1,6,16,59,42 4 | Version=2 5 | ViewMode=1 6 | -------------------------------------------------------------------------------- /classification/regission/data/.directory: -------------------------------------------------------------------------------- 1 | [Dolphin] 2 | AdditionalInfoV2=Details_Size,Details_Date,CustomizedDetails 3 | Timestamp=2013,1,5,14,31,35 4 | Version=2 5 | ViewMode=1 6 | -------------------------------------------------------------------------------- /classification/regission/test/.directory: -------------------------------------------------------------------------------- 1 | [Dolphin] 2 | AdditionalInfoV2=Details_Size,Details_Date,CustomizedDetails 3 | Timestamp=2013,1,6,10,16,7 4 | Version=2 5 | ViewMode=1 6 | -------------------------------------------------------------------------------- /classification/decisiontree/data/species.txt: -------------------------------------------------------------------------------- 1 | "Nonsurfacing?" "Flippers?" "Fish?" 2 | "Yes" "Yes" "Yes" 3 | "Yes" "Yes" "Yes" 4 | "Yes" "No" "No" 5 | "No" "Yes" "No" 6 | "No" "Yes" "No" 7 | -------------------------------------------------------------------------------- /classification/knn/trainingDigits/.directory: -------------------------------------------------------------------------------- 1 | [Dolphin] 2 | AdditionalInfoV2=Details_Size,Details_Date,CustomizedDetails 3 | Timestamp=2012,12,25,18,36,42 4 | Version=2 5 | ViewMode=1 6 | -------------------------------------------------------------------------------- /README: -------------------------------------------------------------------------------- 1 | Frequently used machine learning algorithms implementation in C++. 2 | The description of algorithms come from <>, and I use some of examples from the book's complementary resouces as well. 3 | -------------------------------------------------------------------------------- /common/StringDataReader.cpp: -------------------------------------------------------------------------------- 1 | /** 2 | * Copyright(c) 2012 - 2013 minglin. All rights reserved. 3 | */ 4 | 5 | #include "StringDataReader.h" 6 | 7 | bool StringDataReader::operator()(const std::string& digitStr, std::string& value)const { 8 | value = digitStr; 9 | 10 | return true; 11 | } 12 | -------------------------------------------------------------------------------- /classification/adaboost/WeakClassifier.cpp: -------------------------------------------------------------------------------- 1 | /** 2 | * Copyright(c) 2012 - 2013 minglin. All rights reserved. 3 | */ 4 | 5 | #include "WeakClassifier.h" 6 | 7 | float WeakClassifier::classify(const float* sample, const int feature, const float threshold) { 8 | return sample[feature] > threshold ? 1.0 : -1.0; // categories: -1, 1 9 | } 10 | -------------------------------------------------------------------------------- /common/DataReader.h: -------------------------------------------------------------------------------- 1 | /** 2 | * Copyright(c) 2012 - 2013 minglin. All rights reserved. 3 | */ 4 | 5 | #ifndef _DATA_READER_H_ 6 | #define _DATA_READER_H_ 7 | 8 | #include 9 | 10 | template 11 | class DataReader { 12 | public: 13 | virtual bool operator()(const std::string& digitStr, DataType& value)const = 0; 14 | }; 15 | 16 | #endif 17 | -------------------------------------------------------------------------------- /common/FloatDataReader.h: -------------------------------------------------------------------------------- 1 | /** 2 | * Copyright(c) 2012 - 2013 minglin. All rights reserved. 3 | */ 4 | 5 | #ifndef _FLOAT_DATA_READER_H_ 6 | #define _FLOAT_DATA_READER_H_ 7 | 8 | #include "DataReader.h" 9 | 10 | class FloatDataReader: public DataReader { 11 | public: 12 | bool operator()(const std::string& digitStr, float& value)const; 13 | }; 14 | 15 | #endif 16 | -------------------------------------------------------------------------------- /classification/adaboost/WeakClassifier.h: -------------------------------------------------------------------------------- 1 | /** 2 | * Copyright(c) 2012 - 2013 minglin. All rights reserved. 3 | */ 4 | 5 | #ifndef _WEAK_CLASSIFIER_H_ 6 | #define _WEAK_CLASSIFIER_H_ 7 | 8 | #include "Samples.h" 9 | 10 | class WeakClassifier { 11 | public: 12 | static float classify(const float* samples, const int feature, const float threshold); 13 | }; 14 | 15 | #endif 16 | -------------------------------------------------------------------------------- /classification/regission/RegressionFunction.h: -------------------------------------------------------------------------------- 1 | /** 2 | * Copyright(c) 2012 - 2013 minglin. All rights reserved. 3 | */ 4 | 5 | #ifndef _REGRESSION_FUNCTION_H_ 6 | #define _REGRESSION_FUNCTION_H_ 7 | 8 | class RegressionFunction { 9 | public: 10 | virtual long double operator()(const float* sample, 11 | const long double* params, 12 | int len)const = 0; 13 | }; 14 | 15 | #endif 16 | -------------------------------------------------------------------------------- /classification/regission/Sigmoid.h: -------------------------------------------------------------------------------- 1 | /** 2 | * Copyright(c) 2012 - 2013 minglin. All rights reserved. 3 | */ 4 | 5 | #ifndef _SIGMOID_H_ 6 | #define _SIGMOID_H_ 7 | 8 | #include "RegressionFunction.h" 9 | 10 | class Sigmoid: public RegressionFunction { 11 | public: 12 | long double operator()(const float* sample, const long double* params, int len)const; 13 | }; 14 | 15 | #endif 16 | -------------------------------------------------------------------------------- /common/StringDataReader.h: -------------------------------------------------------------------------------- 1 | /** 2 | * Copyright(c) 2012 - 2013 minglin. All rights reserved. 3 | */ 4 | 5 | #ifndef _STRING_DATA_READER_H_ 6 | #define _STRING_DATA_READER_H_ 7 | 8 | #include "DataReader.h" 9 | 10 | class StringDataReader: public DataReader { 11 | public: 12 | bool operator()(const std::string& digitStr, std::string& value)const; 13 | }; 14 | 15 | #endif 16 | -------------------------------------------------------------------------------- /common/IndexOutOfBound.h: -------------------------------------------------------------------------------- 1 | /** 2 | * Copyright(c) 2012 - 2013 minglin. All rights reserved. 3 | */ 4 | 5 | #ifndef _INDEX_OUT_OF_BOUND_H_ 6 | #define _INDEX_OUT_OF_BOUND_H_ 7 | 8 | #include 9 | 10 | class IndexOutOfBound: public std::exception { 11 | private: 12 | int index; 13 | 14 | public: 15 | IndexOutOfBound(const int index); 16 | const char* what()const throw(); 17 | ~IndexOutOfBound()throw(); 18 | }; 19 | 20 | #endif 21 | -------------------------------------------------------------------------------- /common/IndexOutOfBound.cpp: -------------------------------------------------------------------------------- 1 | /** 2 | * Copyright(c) 2012 - 2013 minglin. All rights reserved. 3 | */ 4 | 5 | #include "IndexOutOfBound.h" 6 | #include 7 | 8 | IndexOutOfBound::IndexOutOfBound(const int index) { 9 | this->index = index; 10 | } 11 | 12 | const char* IndexOutOfBound::what() const throw() { 13 | std::ostringstream msg; 14 | msg<<"IndexOutOfBound: "< 10 | 11 | class AdaptiveBoost { 12 | private: 13 | std::vector weakLearners; 14 | 15 | public: 16 | AdaptiveBoost(const Samples& samples, const float threshold); 17 | float classify(const float* sample)const; 18 | ~AdaptiveBoost(); 19 | }; 20 | 21 | #endif 22 | -------------------------------------------------------------------------------- /classification/decisiontree/data/lenses.data: -------------------------------------------------------------------------------- 1 | 1 1 1 1 1 3 2 | 2 1 1 1 2 2 3 | 3 1 1 2 1 3 4 | 4 1 1 2 2 1 5 | 5 1 2 1 1 3 6 | 6 1 2 1 2 2 7 | 7 1 2 2 1 3 8 | 8 1 2 2 2 1 9 | 9 2 1 1 1 3 10 | 10 2 1 1 2 2 11 | 11 2 1 2 1 3 12 | 12 2 1 2 2 1 13 | 13 2 2 1 1 3 14 | 14 2 2 1 2 2 15 | 15 2 2 2 1 3 16 | 16 2 2 2 2 3 17 | 17 3 1 1 1 3 18 | 18 3 1 1 2 3 19 | 19 3 1 2 1 3 20 | 20 3 1 2 2 1 21 | 21 3 2 1 1 3 22 | 22 3 2 1 2 2 23 | 23 3 2 2 1 3 24 | 24 3 2 2 2 3 25 | -------------------------------------------------------------------------------- /classification/naivebayes/Vector.h: -------------------------------------------------------------------------------- 1 | /** 2 | * Copyright(c) 2012 - 2013 minglin. All rights reserved. 3 | */ 4 | 5 | #ifndef _VECTOR_H_ 6 | #define _VECTOR_H_ 7 | 8 | #include "IndexOutOfBound.h" 9 | 10 | template 11 | class Vector { 12 | private: 13 | DataType* data; 14 | int length; 15 | 16 | public: 17 | Vector(); 18 | Vector(const int len); 19 | Vector(const Vector& vec); 20 | Vector& operator=(const Vector& vec); 21 | DataType& operator[](const int index)throw(IndexOutOfBound); 22 | ~Vector(); 23 | }; 24 | 25 | #endif 26 | -------------------------------------------------------------------------------- /classification/naivebayes/FileTokenizer.h: -------------------------------------------------------------------------------- 1 | /** 2 | * Copyright(c) 2012 - 2013 minglin. All rights reserved. 3 | */ 4 | 5 | #ifndef _FILE_TOKENIZER_H_ 6 | #define _FILE_TOKENIZER_H_ 7 | 8 | #include 9 | #include 10 | 11 | class FileTokenizer { 12 | private: 13 | std::ifstream dataStream; 14 | char line[256]; 15 | int offset; 16 | int length; 17 | 18 | // next token 19 | char token[256]; 20 | 21 | public: 22 | FileTokenizer(const std::string& fileName); 23 | bool hasNext(); 24 | std::string nextToken()const; 25 | ~FileTokenizer(); 26 | }; 27 | 28 | #endif 29 | -------------------------------------------------------------------------------- /classification/regission/Sigmoid.cpp: -------------------------------------------------------------------------------- 1 | /** 2 | * Copyright(c) 2012 - 2013 minglin. All rights reserved. 3 | */ 4 | 5 | #include "Sigmoid.h" 6 | #include "Utils.h" 7 | #ifdef LR_DEBUG 8 | #include 9 | #endif 10 | 11 | /* 12 | * sigmoid(z) = 1 /(e^(-z) + 1). 13 | */ 14 | long double Sigmoid::operator()(const float* sample, const long double* params, int len)const { 15 | long double z = 0.0; 16 | for(int i = 0; i < len; ++i) 17 | z += sample[i] * params[i]; 18 | #ifdef LR_DEBUG 19 | //std::cout<<"z = "< 7 | 8 | float ln(float n) { 9 | return log(n); 10 | } 11 | 12 | float logN(float n, int base) { 13 | return log(n)/log(base); 14 | } 15 | 16 | float pow(int z) { 17 | return pow(2, z / log(2)); 18 | } 19 | 20 | float pow(float z) { 21 | return pow(2, z / log(2)); 22 | } 23 | 24 | long double pow(long double z) { 25 | return pow(2, z / log(2)); 26 | } 27 | 28 | float min(float x, float y) { 29 | return x < y ? x : y; 30 | } 31 | 32 | float max(float x, float y) { 33 | return min(y, x); 34 | } 35 | -------------------------------------------------------------------------------- /classification/knn/makefile: -------------------------------------------------------------------------------- 1 | SRC_DIR=$(HOME)/ml 2 | 3 | CXX=g++ 4 | #CXXFLAGS=-c -g -W -I$(SRC_DIR)/utility -I. 5 | CXXFLAGS=-c -O2 -W -I$(SRC_DIR)/utility -I. -DCHECK_IO 6 | 7 | TESTER=KNearestNeighboursTester 8 | SRCS=NMinHeap.cpp \ 9 | InputDataSet.cpp \ 10 | KNearestNeighbours.cpp \ 11 | $(SRC_DIR)/utility/Timing.cpp \ 12 | test/$(TESTER).cpp 13 | 14 | OBJS=NMinHeap.o \ 15 | InputDataSet.o \ 16 | KNearestNeighbours.o \ 17 | $(SRC_DIR)/utility/Timing.o \ 18 | test/$(TESTER).o 19 | 20 | .PHONY: knn 21 | $(TESTER): $(OBJS) 22 | $(CXX) $^ -o $@ 23 | 24 | $(OBJS): %.o : %.cpp 25 | $(CXX) $(CXXFLAGS) $< -o $@ 26 | 27 | .PHONY: clean 28 | clean: 29 | rm $(OBJS) $(TESTER) 30 | -------------------------------------------------------------------------------- /clustering/apriori/makefile: -------------------------------------------------------------------------------- 1 | SRC_DIR=$(HOME)/ml 2 | 3 | CXX=g++ 4 | CXXFLAGS=-c -g -W -I$(SRC_DIR)/common -I$(SRC_DIR)/utility -I. -DAP_DBG 5 | #CXXFLAGS=-c -W -I$(SRC_DIR)/common -I$(SRC_DIR)/utility -I. -O2 6 | 7 | TESTER=AprioriTester 8 | SRCS=$(SRC_DIR)/common/IndexOutOfBound.cpp \ 9 | $(SRC_DIR)/utility/Timing.cpp \ 10 | Apriori.cpp \ 11 | test/$(TESTER).cpp 12 | 13 | OBJS=$(SRC_DIR)/common/IndexOutOfBound.o \ 14 | $(SRC_DIR)/utility/Timing.o \ 15 | Apriori.o \ 16 | test/$(TESTER).o 17 | 18 | .PHONY: apriori 19 | $(TESTER): $(OBJS) 20 | $(CXX) $^ -o $@ 21 | 22 | $(OBJS): %.o : %.cpp 23 | $(CXX) $(CXXFLAGS) $< -o $@ 24 | 25 | .PHONY: clean 26 | clean: 27 | rm -f $(OBJS) $(TESTER) 28 | -------------------------------------------------------------------------------- /utility/Utils.h: -------------------------------------------------------------------------------- 1 | /** 2 | * Copyright(c) 2012 - 2013 minglin. All rights reserved. 3 | */ 4 | 5 | #ifndef _UTILS_H_ 6 | 7 | float ln(float n); 8 | 9 | /* 10 | * The natural logarithm in C++, that is, function 'log' defined in cmatch, is the base-e logarithm. 11 | * Since logN(x) = logY(x)/logY(N), we can calculate any base logarithm using the base-e logrithm. 12 | * For example, log2(x) = log(x)/log(2). 13 | */ 14 | float logN(float n, int base); 15 | 16 | /* 17 | * e^z = (2^logN(e, 2))^z = 2^(z / logN(e, 2)); 18 | */ 19 | float pow(int z); 20 | float pow(float z); 21 | long double pow(long double z); 22 | 23 | float min(float x, float y); 24 | float max(float x, float y); 25 | 26 | #endif 27 | -------------------------------------------------------------------------------- /classification/naivebayes/test/OfflineNBCTester.cpp: -------------------------------------------------------------------------------- 1 | /** 2 | * Copyright(c) 2012 - 2013 minglin. All rights reserved. 3 | */ 4 | 5 | #include "OfflineNaiveBayesClassifier.h" 6 | #include "FileTokenizer.h" 7 | #include 8 | 9 | int main(int argc, char** argv) { 10 | std::string trainingDir = "data//training"; 11 | std::string doc = "data//test//posting.txt"; 12 | /* 13 | FileTokenizer tokenizer(doc); 14 | while(tokenizer.hasNext()) { 15 | std::string token = tokenizer.nextToken(); 16 | std::cout< 10 | 11 | int main(int argc, char** argv) { 12 | std::string dataFile = "data/species.txt"; 13 | Samples trainingSamples(dataFile, StringDataReader()); 14 | 15 | int64 start = getTimeMs64(); 16 | DecisionTree decisionTree(trainingSamples); 17 | //for(int i = 0; i < 1000; ++i) { 18 | decisionTree.breadthFirstTraverse(); 19 | //} 20 | std::cout<<"execution time: "< 9 | 10 | class WeakLearner { 11 | private: 12 | static float INFINITESIMAL; 13 | 14 | int feature; 15 | float threshold; 16 | float alpha; 17 | 18 | public: 19 | WeakLearner(); 20 | float train(const Samples& samples, const float* categories, 21 | const std::pair* featureRanges, const int stepNum, float* weights); 22 | inline int getFeature()const { 23 | return feature; 24 | } 25 | inline float getThreshold()const { 26 | return threshold; 27 | } 28 | float getAlpha()const { 29 | return alpha; 30 | } 31 | ~WeakLearner(); 32 | }; 33 | 34 | #endif 35 | -------------------------------------------------------------------------------- /classification/knn/NMinHeap.h: -------------------------------------------------------------------------------- 1 | /** 2 | * Copyright(c) 2012 - 2013 minglin. All rights reserved. 3 | */ 4 | 5 | #ifndef _N_MIN_HEAP_H_ 6 | #define _N_MIN_HEAP_H_ 7 | 8 | #include 9 | 10 | /* 11 | * NMinHeap maintains N minimum elements with the maximum one among the N elements in root. 12 | */ 13 | template 14 | class NMinHeap { 15 | private: 16 | std::pair* pairs; 17 | int capacity; 18 | int num; 19 | 20 | public: 21 | typedef std::pair* iterator; 22 | 23 | NMinHeap(int n); 24 | bool insert(const K& k, const V& v); 25 | // iterate the heap like an array 26 | int size()const; 27 | std::pair operator[](int index)const; 28 | ~NMinHeap(); 29 | 30 | private: 31 | inline void swap(std::pair* pair1, std::pair* pair2); 32 | }; 33 | 34 | #endif 35 | -------------------------------------------------------------------------------- /classification/knn/test/NMinHeapTester.cpp: -------------------------------------------------------------------------------- 1 | /** 2 | * Copyright(c) 2012 - 2013 minglin. All rights reserved. 3 | */ 4 | 5 | #include "NMinHeap.cpp" 6 | #include 7 | 8 | int main(int argc, char** argv) { 9 | NMinHeap nmh(5); 10 | std::pair elems[] = { 11 | std::make_pair(3.0, 2), std::make_pair(3.3, 1), std::make_pair(1.2, 3), 12 | std::make_pair(2.5, 4), std::make_pair(4.2, 3), std::make_pair(3.0, 5), 13 | std::make_pair(2.0, 4), std::make_pair(1.8, 5), std::make_pair(4.5, 2), 14 | std::make_pair(5.8, 5) 15 | }; 16 | 17 | for(int i = 0; i < 10; ++i) 18 | nmh.insert(elems[i].first, elems[i].second); 19 | int size = nmh.size(); 20 | for(int i = 0; i < size; ++i) 21 | std::cout<<"("< 10 | #include 11 | #include 12 | 13 | class InputDataSet { 14 | private: 15 | std::string dirName; 16 | std::map > docs; 17 | int categoryNum; 18 | 19 | public: 20 | InputDataSet(const std::string& dir); 21 | // A member function returns reference to a member variable can't be constant 22 | std::string& getDir(); 23 | std::vector& getDocuments(const int category) throw(IndexOutOfBound); 24 | int getCategoryNum()const; 25 | ~InputDataSet(); 26 | 27 | private: 28 | void readDir(); 29 | int parse(const std::string& fileName)const; 30 | }; 31 | 32 | #endif 33 | -------------------------------------------------------------------------------- /classification/knn/test/InputDataSetTester.cpp: -------------------------------------------------------------------------------- 1 | /** 2 | * Copyright(c) 2012 - 2013 minglin. All rights reserved. 3 | */ 4 | 5 | #include "InputDataSet.h" 6 | #include 7 | 8 | int main(int argc, char** argv) { 9 | InputDataSet ids("trainingDigits"); 10 | 11 | int samplesCount = 0; 12 | while(ids.hasNext() && (samplesCount++ < 3)) { 13 | std::vector > samples = ids.next(); 14 | int sampleDim = InputDataSet::SAMPLE_DIM; 15 | 16 | int sampleCount = 0; 17 | int sampleNum = samples.size(); 18 | for(int i = 0; (i < sampleNum) && (sampleCount < 3); ++i, ++sampleCount) { 19 | std::bitset<1024> sample = samples[i]; 20 | for(int j = 0; j < sampleDim; ++j) { 21 | int startIdx = j*sampleDim; 22 | for(int k = 0; k < sampleDim; ++k) 23 | std::cout< 9 | 10 | int main(int argc, char** argv) { 11 | std::string dataFile("data/testSet.txt"); 12 | //std::string dataFile("data/points.txt"); 13 | Samples samples(dataFile, FloatDataReader()); 14 | /* 15 | int featureNum = samples.getFeatureNum(); 16 | int sampleNum = samples.getSampleNum(); 17 | for(int i = 0; i < sampleNum; ++i) { 18 | const float* sample = samples.getSample(i); 19 | for(int j = 0; j < featureNum; ++j) 20 | std::cout< 9 | #include 10 | #include 11 | #ifndef CHECK_IO 12 | #include 13 | #endif 14 | 15 | class InputDataSet { 16 | public: 17 | static const int DIGIT_NUM = 10; 18 | static const int SAMPLE_DIM = 32; 19 | 20 | private: 21 | std::string dataDir; 22 | std::vector > digits[DIGIT_NUM]; 23 | int nextIdx; 24 | 25 | public: 26 | InputDataSet(std::string dir); 27 | bool hasNext(); 28 | std::vector >& next(); 29 | ~InputDataSet(); 30 | 31 | private: 32 | #ifdef CHECK_IO 33 | bool readSample(std::string sampleFile, std::bitset<1024>& sample); 34 | #else 35 | bool readSample(std::string sampleFile, std::ostringstream& sample); 36 | #endif 37 | }; 38 | 39 | #endif 40 | -------------------------------------------------------------------------------- /classification/knn/test/KNearestNeighboursTester.cpp: -------------------------------------------------------------------------------- 1 | /** 2 | * Copyright(c) 2012 - 2013 minglin. All rights reserved. 3 | */ 4 | 5 | #include "KNearestNeighbours.h" 6 | #include "Timing.h" 7 | #include 8 | 9 | int main(int argc, char** argv) { 10 | std::string trainingDir = "trainingDigits"; 11 | std::string testDir = "testDigits"; 12 | //int k = 21; 13 | int k = 3; 14 | int64 start = getTimeMs64(); 15 | InputDataSet trainingSet(trainingDir), testSet(testDir); 16 | std::cout<<"Execution time of creating training and test sets: "<& testSample); 26 | float getErrorRate() const; 27 | ~KNearestNeighbours(); 28 | 29 | private: 30 | float distance(const std::bitset<1024>& sample1, const std::bitset<1024>& sample2)const; 31 | }; 32 | 33 | #endif 34 | -------------------------------------------------------------------------------- /classification/decisiontree/makefile: -------------------------------------------------------------------------------- 1 | SRC_DIR=$(HOME)/ml 2 | 3 | CXX=g++ 4 | #CXXFLAGS=-c -g -W -I. -I$(SRC_DIR)/common -I$(SRC_DIR)/utility 5 | CXXFLAGS=-c -W -I$(SRC_DIR)/common -I$(SRC_DIR)/utility -I. -O2 6 | 7 | TESTER=DecisionTreeTester 8 | SRCS=$(SRC_DIR)/common/IndexOutOfBound.cpp \ 9 | $(SRC_DIR)/common/StringDataReader.cpp \ 10 | $(SRC_DIR)/common/Samples.cpp \ 11 | $(SRC_DIR)/utility/Timing.cpp \ 12 | $(SRC_DIR)/utility/Utils.cpp \ 13 | Node.cpp \ 14 | DecisionTree.cpp \ 15 | test/$(TESTER).cpp 16 | 17 | OBJS=$(SRC_DIR)/common/IndexOutOfBound.o \ 18 | $(SRC_DIR)/common/StringDataReader.o \ 19 | $(SRC_DIR)/common/Samples.o \ 20 | $(SRC_DIR)/utility/Timing.o \ 21 | $(SRC_DIR)/utility/Utils.o \ 22 | Node.o \ 23 | DecisionTree.o \ 24 | test/$(TESTER).o 25 | 26 | .PHONY: dt 27 | $(TESTER): $(OBJS) 28 | $(CXX) $^ -o $@ 29 | 30 | $(OBJS): %.o : %.cpp 31 | $(CXX) $(CXXFLAGS) $< -o $@ 32 | 33 | .PHONY: clean 34 | clean: 35 | rm -f $(OBJS) $(TESTER) 36 | -------------------------------------------------------------------------------- /classification/naivebayes/makefile: -------------------------------------------------------------------------------- 1 | SRC_DIR=$(HOME)/ml 2 | 3 | CXX=g++ 4 | CXXFLAGS=-c -g -W -I$(SRC_DIR)/common -I$(SRC_DIR)/utility -I/usr/include -I. -DNBC_DEBUG -DUSE_VECTOR 5 | #CXXFLAGS=-c -O2 -W -I$(SRC_DIR)/common -I$(SRC_DIR)/utility -I/usr/include -I. 6 | 7 | TESTER=OfflineNBCTester 8 | SRCS=$(SRC_DIR)/common/IndexOutOfBound.cpp \ 9 | $(SRC_DIR)/utility/Timing.cpp \ 10 | $(SRC_DIR)/utility/Utils.cpp \ 11 | Vector.cpp \ 12 | InputDataSet.cpp \ 13 | FileTokenizer.cpp \ 14 | OfflineNaiveBayesClassifier.cpp \ 15 | test/$(TESTER).cpp 16 | 17 | OBJS=$(SRC_DIR)/common/IndexOutOfBound.o \ 18 | $(SRC_DIR)/utility/Timing.o \ 19 | $(SRC_DIR)/utility/Utils.o \ 20 | Vector.o \ 21 | InputDataSet.o \ 22 | FileTokenizer.o \ 23 | OfflineNaiveBayesClassifier.o \ 24 | test/$(TESTER).o 25 | 26 | .PHONY: nbc 27 | $(TESTER): $(OBJS) 28 | $(CXX) $^ -o $@ 29 | 30 | $(OBJS): %.o : %.cpp 31 | $(CXX) $(CXXFLAGS) $< -o $@ 32 | 33 | .PHONY: clean 34 | clean: 35 | rm -f $(OBJS) $(TESTER) 36 | -------------------------------------------------------------------------------- /classification/regission/LogisticRegression.h: -------------------------------------------------------------------------------- 1 | /** 2 | * Copyright(c) 2012 - 2013 minglin. All rights reserved. 3 | */ 4 | 5 | #ifndef _LOGISTIC_REGRESSION_H_ 6 | #define _LOGISTIC_REGRESSION_H_ 7 | 8 | #include "Samples.h" 9 | #include "RegressionFunction.h" 10 | 11 | class LogisticRegression { 12 | private: 13 | Samples trainingSamples; 14 | int featureNum; 15 | int sampleNum; 16 | float* categories; 17 | float categoryRange; 18 | const RegressionFunction& rf; 19 | float threshold; 20 | 21 | float alpha; 22 | long double* parameters; 23 | 24 | public: 25 | LogisticRegression(const Samples& samples, const float a, 26 | const RegressionFunction& regFunc, float threshold); 27 | int classify(const float* testSample); 28 | ~LogisticRegression(); 29 | 30 | private: 31 | // return: iterations to reach convergence. 32 | int gradientAscent(); 33 | void stochasticGradientAscent(); 34 | bool convergent(const long double* deviations, 35 | const float categoryRange)const; 36 | }; 37 | 38 | #endif 39 | -------------------------------------------------------------------------------- /classification/regission/makefile: -------------------------------------------------------------------------------- 1 | SRC_DIR=$(HOME)/ml 2 | 3 | CXX=g++ 4 | CXXFLAGS=-c -g -W -I$(SRC_DIR)/common -I$(SRC_DIR)/utility -I/usr/include -I. -DLR_DEBUG 5 | #CXXFLAGS=-c -O2 -W -I$(SRC_DIR)/common -I$(SRC_DIR)/utility -I/usr/include -I. 6 | 7 | TESTER=LogisticRegressionTester 8 | SRCS=$(SRC_DIR)/common/IndexOutOfBound.cpp \ 9 | $(SRC_DIR)/common/FloatDataReader.cpp \ 10 | $(SRC_DIR)/common/Samples.cpp \ 11 | $(SRC_DIR)/utility/Timing.cpp \ 12 | $(SRC_DIR)/utility/Utils.cpp \ 13 | Sigmoid.cpp \ 14 | LogisticRegression.cpp \ 15 | test/$(TESTER).cpp 16 | 17 | OBJS=$(SRC_DIR)/common/IndexOutOfBound.o \ 18 | $(SRC_DIR)/common/FloatDataReader.o \ 19 | $(SRC_DIR)/common/Samples.o \ 20 | $(SRC_DIR)/utility/Timing.o \ 21 | $(SRC_DIR)/utility/Utils.o \ 22 | Sigmoid.o \ 23 | LogisticRegression.o \ 24 | test/$(TESTER).o 25 | 26 | .PHONY: lr 27 | $(TESTER): $(OBJS) 28 | $(CXX) $^ -o $@ 29 | 30 | $(OBJS): %.o : %.cpp 31 | $(CXX) $(CXXFLAGS) $< -o $@ 32 | 33 | .PHONY: clean 34 | clean: 35 | rm -f $(OBJS) $(TESTER) 36 | -------------------------------------------------------------------------------- /clustering/kmeans/OfflineKMeans.h: -------------------------------------------------------------------------------- 1 | /** 2 | * Copyright(c) 2012 - 2013 minglin. All rights reserved. 3 | */ 4 | 5 | #ifndef _OFFLINE_K_MEANS_H_ 6 | #define _OFFLINE_K_MEANS_H_ 7 | 8 | #include "Samples.h" 9 | #include 10 | #include 11 | 12 | class OfflineKMeans { 13 | private: 14 | const Samples& samples; 15 | int featureNum; 16 | int sampleNum; 17 | std::pair >* clusters; 18 | int clusterNum; 19 | /* 20 | * Mapping from samples to clusters. clusterIndexes[i] means sample indexed by 'i' 21 | * is in cluster indexed by 'clusterIndexes[i]'. 22 | */ 23 | int* clusterIndexes; 24 | 25 | public: 26 | OfflineKMeans(const Samples& data, const int k); 27 | void print()const; 28 | ~OfflineKMeans(); 29 | 30 | private: 31 | void initClusters(); 32 | bool reCluster(); 33 | void updateCentroids(); 34 | int cluster(const float* sample, const int len)const; 35 | float distance(const float* sample1, const float* sample2, const int len)const; 36 | }; 37 | 38 | #endif 39 | -------------------------------------------------------------------------------- /classification/adaboost/makefile: -------------------------------------------------------------------------------- 1 | SRC_DIR=$(HOME)/ml 2 | 3 | CXX=g++ 4 | CXXFLAGS=-c -g -W -I$(SRC_DIR)/common -I$(SRC_DIR)/utility -I. -DAB_DEBUG 5 | #CXXFLAGS=-c -W -I$(SRC_DIR)/common -I$(SRC_DIR)/utility -I. -O2 6 | 7 | TESTER=AdaptiveBoostTester 8 | SRCS=$(SRC_DIR)/common/IndexOutOfBound.cpp \ 9 | $(SRC_DIR)/common/FloatDataReader.cpp \ 10 | $(SRC_DIR)/common/Samples.cpp \ 11 | $(SRC_DIR)/utility/Timing.cpp \ 12 | $(SRC_DIR)/utility/Utils.cpp \ 13 | WeakClassifier.cpp \ 14 | WeakLearner.cpp \ 15 | AdaptiveBoost.cpp \ 16 | test/$(TESTER).cpp 17 | 18 | OBJS=$(SRC_DIR)/common/IndexOutOfBound.o \ 19 | $(SRC_DIR)/common/FloatDataReader.o \ 20 | $(SRC_DIR)/common/Samples.o \ 21 | $(SRC_DIR)/utility/Timing.o \ 22 | $(SRC_DIR)/utility/Utils.o \ 23 | WeakClassifier.o \ 24 | WeakLearner.o \ 25 | AdaptiveBoost.o \ 26 | test/$(TESTER).o 27 | 28 | .PHONY: lr 29 | $(TESTER): $(OBJS) 30 | $(CXX) $^ -o $@ 31 | 32 | $(OBJS): %.o : %.cpp 33 | $(CXX) $(CXXFLAGS) $< -o $@ 34 | 35 | .PHONY: clean 36 | clean: 37 | rm -f $(OBJS) $(TESTER) 38 | -------------------------------------------------------------------------------- /classification/regission/test/LogisticRegressionTester.cpp: -------------------------------------------------------------------------------- 1 | /** 2 | * Copyright(c) 2012 - 2013 minglin. All rights reserved. 3 | */ 4 | 5 | #include "FloatDataReader.h" 6 | #include "Samples.cpp" 7 | #include "Sigmoid.h" 8 | #include "LogisticRegression.h" 9 | #include 10 | 11 | int main(int argc, char** argv) { 12 | std::string trainingFile = "data/horseColicTraining.txt"; 13 | Samples trainingSamples(trainingFile, FloatDataReader()); 14 | float alpha = 0.01; 15 | Sigmoid sigmoid; 16 | float threshold = 0.5; 17 | LogisticRegression lr(trainingSamples, alpha, sigmoid, threshold); 18 | 19 | /* 20 | std::string testFile = "data/horseColicTest.txt"; 21 | Samples testSamples(testFile, lrConverter); 22 | int featureNum = testSamples.getFeatureNum(); 23 | int testSampleNum = testSamples.getSampleNum(); 24 | for(int i = 0; i < testSampleNum; ++i) { 25 | const float* testSample = testSamples.getSample(i); 26 | int category = lr.classify(testSample); 27 | std::cout<<"sample "< 7 | 8 | int main(int argc, char** argv) { 9 | /* 10 | * 1- [0.4, {Item0}] [0.4, {Item1}] [0.8, {Item2}] 11 | * [0.6, {Item3}] [0.4, {Item4}] [0.6, {Item5}] 12 | * 2- [0.4, {Item0, Item2}] [0.4, {Item1, Item2}] 13 | * [0.4, {Item2, Item3}] [0.6, {Item2, Item5}] 14 | * [0.4, {Item3, Item5}] 15 | * 3- [0.4, {Item2, Item3, Item5}] 16 | */ 17 | std::string transactions[5][4] = { 18 | {"Item0", "Item2", "Item3", "Item5"}, 19 | {"Item1", "Item2", "Item4", "Item5"}, 20 | {"Item2", "Item3", "Item5", ""}, 21 | {"Item0", "Item1", "Item2", ""}, 22 | {"Item3", "Item4", "" , ""} 23 | }; 24 | std::vector > data; 25 | for(int i = 0; i < 5; ++i) { 26 | std::set line; 27 | for(int j = 0; j < 4; ++j) { 28 | if(transactions[i][j] != "") 29 | line.insert(transactions[i][j]); 30 | } 31 | data.push_back(line); 32 | } 33 | float threshold = 0.4; 34 | Apriori apriori(data, 0.4); 35 | apriori.print(); 36 | 37 | return 0; 38 | } 39 | -------------------------------------------------------------------------------- /classification/naivebayes/FileTokenizer.cpp: -------------------------------------------------------------------------------- 1 | /** 2 | * Copyright(c) 2012 - 2013 minglin. All rights reserved. 3 | */ 4 | 5 | #include "FileTokenizer.h" 6 | #include 7 | #include 8 | 9 | FileTokenizer::FileTokenizer(const std::string& fileName): dataStream(fileName.c_str()) { 10 | if(!dataStream) 11 | throw std::runtime_error("Unable to open file " + fileName + "!"); 12 | 13 | dataStream.getline(line, 256); 14 | offset = 0; 15 | length = strlen(line); 16 | } 17 | 18 | bool FileTokenizer::hasNext() { 19 | if(offset >= length) { 20 | dataStream.getline(line, 256); 21 | if(dataStream.eof() == true) 22 | return false; 23 | 24 | offset = 0; 25 | length = strlen(line); 26 | } 27 | 28 | int i = 0; 29 | while(offset < length) { 30 | if(line[offset] == ' ') 31 | break; 32 | 33 | token[i++] = line[offset++]; 34 | } 35 | token[i] = '\0'; 36 | // skip following spaces 37 | while((offset < length) && (line[++offset] == ' ')); 38 | 39 | return true; 40 | } 41 | 42 | std::string FileTokenizer::nextToken()const { 43 | return std::string(token); 44 | } 45 | 46 | 47 | FileTokenizer::~FileTokenizer() { 48 | dataStream.close(); 49 | } 50 | 51 | -------------------------------------------------------------------------------- /classification/knn/testDigits/0_0.txt: -------------------------------------------------------------------------------- 1 | 00000000000001100000000000000000 2 | 00000000000011111100000000000000 3 | 00000000000111111111000000000000 4 | 00000000011111111111000000000000 5 | 00000001111111111111100000000000 6 | 00000000111111100011110000000000 7 | 00000001111110000001110000000000 8 | 00000001111110000001110000000000 9 | 00000011111100000001110000000000 10 | 00000011111100000001111000000000 11 | 00000011111100000000011100000000 12 | 00000011111100000000011100000000 13 | 00000011111000000000001110000000 14 | 00000011111000000000001110000000 15 | 00000001111100000000000111000000 16 | 00000001111100000000000111000000 17 | 00000001111100000000000111000000 18 | 00000011111000000000000111000000 19 | 00000011111000000000000111000000 20 | 00000000111100000000000011100000 21 | 00000000111100000000000111100000 22 | 00000000111100000000000111100000 23 | 00000000111100000000001111100000 24 | 00000000011110000000000111110000 25 | 00000000011111000000001111100000 26 | 00000000011111000000011111100000 27 | 00000000011111000000111111000000 28 | 00000000011111100011111111000000 29 | 00000000000111111111111110000000 30 | 00000000000111111111111100000000 31 | 00000000000011111111110000000000 32 | 00000000000000111110000000000000 33 | -------------------------------------------------------------------------------- /classification/knn/testDigits/0_1.txt: -------------------------------------------------------------------------------- 1 | 00000000000000011000000000000000 2 | 00000000000111111110000000000000 3 | 00000000001111111111100000000000 4 | 00000000001111111111110000000000 5 | 00000000011111111111111000000000 6 | 00000000011111100011111000000000 7 | 00000000111110000001111000000000 8 | 00000000111110000001111100000000 9 | 00000000111110000000111110000000 10 | 00000001111110000000111110000000 11 | 00000001111110000000011111000000 12 | 00000001111110000000001111000000 13 | 00000001111110000000001111100000 14 | 00000001111100000000001111000000 15 | 00000001111000000000001111000000 16 | 00000001111000000000001111000000 17 | 00000001111000000000000111000000 18 | 00000000111100000000000111000000 19 | 00000000111100000000000111000000 20 | 00000000111100000000000111000000 21 | 00000001111000000000011110000000 22 | 00000001111000000000011110000000 23 | 00000000111000000000011110000000 24 | 00000000111110000011111110000000 25 | 00000000111110001111111100000000 26 | 00000000111111111111111000000000 27 | 00000000011111111111111000000000 28 | 00000000111111111111100000000000 29 | 00000000011111111111000000000000 30 | 00000000001111111000000000000000 31 | 00000000001111100000000000000000 32 | 00000000000100000000000000000000 33 | -------------------------------------------------------------------------------- /classification/knn/testDigits/0_10.txt: -------------------------------------------------------------------------------- 1 | 00000000000100000000000000000000 2 | 00000000001111000000000000000000 3 | 00000000001111000000000000000000 4 | 00000000011111100000000000000000 5 | 00000000111111111111000000000000 6 | 00000000011111111111110000000000 7 | 00000000111111111111110000000000 8 | 00000000111111111111111000000000 9 | 00000000111111111111111000000000 10 | 00000001111111111111111000000000 11 | 00000000111111111111111110000000 12 | 00000001111111111001111110000000 13 | 00000001111100000000111110000000 14 | 00000001111100000000011110000000 15 | 00000001111100000000001111000000 16 | 00000001111100000000001111000000 17 | 00000001111000000000001111000000 18 | 00000001111000000000011111000000 19 | 00000001111000000000011111000000 20 | 00000000111100000000011111100000 21 | 00000001111100000000111111000000 22 | 00000001111100000001111111000000 23 | 00000001111000000011111110000000 24 | 00000000111100000011111111000000 25 | 00000000111100000011111111000000 26 | 00000000111111111111111110000000 27 | 00000000111111111111111100000000 28 | 00000000011111111111111100000000 29 | 00000000001111111111111100000000 30 | 00000000001111111111110000000000 31 | 00000000000111111111100000000000 32 | 00000000000011111100000000000000 33 | -------------------------------------------------------------------------------- /classification/knn/testDigits/0_11.txt: -------------------------------------------------------------------------------- 1 | 00000000000000101100000000000000 2 | 00000000000011111110000000000000 3 | 00000000000111111111000000000000 4 | 00000000000111111111110000000000 5 | 00000000000111111111111000000000 6 | 00000000001111110011111000000000 7 | 00000000011111110000111100000000 8 | 00000000011111110000011100000000 9 | 00000000111110000000011110000000 10 | 00000000111100000000001110000000 11 | 00000000111000000000001110000000 12 | 00000001111000000000001110000000 13 | 00000001111000000000001110000000 14 | 00000001110000000000001111000000 15 | 00000001110000000000000111000000 16 | 00000001110000000000000111000000 17 | 00000011110000000000000111000000 18 | 00000011110000000000000111000000 19 | 00000011110000000000000111000000 20 | 00000011110000000000000111000000 21 | 00000001110000000000000111000000 22 | 00000001110000000000000111000000 23 | 00000001110000000000000111000000 24 | 00000001111000000000000111000000 25 | 00000000111100000000001111000000 26 | 00000000111110000000001111000000 27 | 00000000111111100000111111000000 28 | 00000000011111111111111110000000 29 | 00000000000111111111111110000000 30 | 00000000000111111111111100000000 31 | 00000000000000111111111110000000 32 | 00000000000000001111111000000000 33 | -------------------------------------------------------------------------------- /classification/knn/testDigits/0_12.txt: -------------------------------------------------------------------------------- 1 | 00000000000000000111000000000000 2 | 00000000000000111111000000000000 3 | 00000000000011111111100000000000 4 | 00000000000011111111110000000000 5 | 00000000000011111111111000000000 6 | 00000000110111111111111000000000 7 | 00000001111111111111111000000000 8 | 00000001111111100000111000000000 9 | 00000001111111000000011110000000 10 | 00000001111110000000011110000000 11 | 00000001111110000000001110000000 12 | 00000011111100000000001110000000 13 | 00000011111100000000001110000000 14 | 00000011111000000000001110000000 15 | 00000001111100000000000111000000 16 | 00000011111000000000000111000000 17 | 00000011111000000000001110000000 18 | 00000011111000000000001110000000 19 | 00000011110000000000011110000000 20 | 00000001111000000000001111000000 21 | 00000000111100000000001111000000 22 | 00000000111100000000001110000000 23 | 00000000111100000000011110000000 24 | 00000000111110000000111110000000 25 | 00000000111111000000111100000000 26 | 00000000001111100000111110000000 27 | 00000000001111111111111110000000 28 | 00000000000111111111111000000000 29 | 00000000000111111111111000000000 30 | 00000000000011111111110000000000 31 | 00000000000000111111110000000000 32 | 00000000000000011111100000000000 33 | -------------------------------------------------------------------------------- /classification/knn/testDigits/0_13.txt: -------------------------------------------------------------------------------- 1 | 00000000000000111100000000000000 2 | 00000000000011111110000000000000 3 | 00000000000111111111000000000000 4 | 00000000001111111111100000000000 5 | 00000000001111111111100000000000 6 | 00000000111111111111110000000000 7 | 00000000011111111111111000000000 8 | 00000000111111110111111000000000 9 | 00000001111110000000111100000000 10 | 00000001111110000000011100000000 11 | 00000011111110000000011100000000 12 | 00000011111100000000011100000000 13 | 00000011111100000000011100000000 14 | 00000001111100000000001111000000 15 | 00000001111000000000000111000000 16 | 00000011110000000000000111000000 17 | 00000011110000000000000111000000 18 | 00000011110000000000000111000000 19 | 00000011110000000000000111000000 20 | 00000011110000000000000111000000 21 | 00000000111000000000000011100000 22 | 00000000111000000000000011100000 23 | 00000000111100000000000111100000 24 | 00000000111100000000000111100000 25 | 00000000111110000000011111100000 26 | 00000000011111000000111111000000 27 | 00000000011111111111111110000000 28 | 00000000001111111111111111000000 29 | 00000000000111111111111111000000 30 | 00000000000111111111111110000000 31 | 00000000000011111111111000000000 32 | 00000000000000111111110000000000 33 | -------------------------------------------------------------------------------- /classification/knn/testDigits/0_14.txt: -------------------------------------------------------------------------------- 1 | 00000000000000111100000000000000 2 | 00000000000001111110000000000000 3 | 00000000000111111111000000000000 4 | 00000000000011111111110000000000 5 | 00000000000111111111111000000000 6 | 00000000000111111111111000000000 7 | 00000000000111111111111000000000 8 | 00000000001111100001111100000000 9 | 00000000001111000000111100000000 10 | 00000000011110000000111100000000 11 | 00000000111110000000011100000000 12 | 00000001111110000000011110000000 13 | 00000000111111000000001111000000 14 | 00000001111111000000001111000000 15 | 00000001111111000000001111000000 16 | 00000001111110000000001111000000 17 | 00000001111000000000001111000000 18 | 00000001110000000000001111000000 19 | 00000001110000000000001111000000 20 | 00000001110000000000001111000000 21 | 00000011110000000000001111000000 22 | 00000000111000000000000111100000 23 | 00000000111100000000000111100000 24 | 00000000111110000000011111100000 25 | 00000000111111000000111111000000 26 | 00000000111111110001111111000000 27 | 00000000011111111111111111000000 28 | 00000000011111111111111110000000 29 | 00000000001111111111111100000000 30 | 00000000000111111111111000000000 31 | 00000000000001111111110000000000 32 | 00000000000000011111000000000000 33 | -------------------------------------------------------------------------------- /classification/knn/testDigits/0_15.txt: -------------------------------------------------------------------------------- 1 | 00000000000000111110000000000000 2 | 00000000000011111111000000000000 3 | 00000000000111111111100000000000 4 | 00000000000111111111110000000000 5 | 00000000001111111111111000000000 6 | 00000000001111111111111000000000 7 | 00000000011111111111111000000000 8 | 00000000111111000011111100000000 9 | 00000000111110000001111100000000 10 | 00000000111100000000111100000000 11 | 00000000111111000000011111000000 12 | 00000000111110000000001111000000 13 | 00000000111110000000001111000000 14 | 00000001111110000000001111000000 15 | 00000001111110000000001111000000 16 | 00000001111110000000000111000000 17 | 00000011111100000000000111000000 18 | 00000001111000000000000111000000 19 | 00000001111000000000000111000000 20 | 00000001111000000000000111000000 21 | 00000001111000000000000111000000 22 | 00000001111000000000001111000000 23 | 00000001111000000000011111000000 24 | 00000000111110000000001111100000 25 | 00000000111110000000011111000000 26 | 00000000011111000011111111000000 27 | 00000000011111111111111111000000 28 | 00000000001111111111111100000000 29 | 00000000001111111111111100000000 30 | 00000000000111111111111000000000 31 | 00000000000111111111100000000000 32 | 00000000000001111110000000000000 33 | -------------------------------------------------------------------------------- /classification/knn/testDigits/0_16.txt: -------------------------------------------------------------------------------- 1 | 00000000000100000000000000000000 2 | 00000000001100011111000000000000 3 | 00000000011110011111110000000000 4 | 00000000111111111111100000000000 5 | 00000000111111111111110000000000 6 | 00000000111111111111110000000000 7 | 00000000111111111111111000000000 8 | 00000000111111111111111100000000 9 | 00000000111111100000111110000000 10 | 00000000111111000000011110000000 11 | 00000000111100000000011111000000 12 | 00000000111000000000001111100000 13 | 00000011110000000000011111000000 14 | 00000011110000000000011111000000 15 | 00000011110000000000011111000000 16 | 00000011110000000000001111000000 17 | 00000011110000000000001111000000 18 | 00000011110000000000001111000000 19 | 00000011110000000000001111000000 20 | 00000011110000000000001111000000 21 | 00000011110000000000011111000000 22 | 00000111110000000000111110000000 23 | 00000011110000000001111110000000 24 | 00000011111000000001111110000000 25 | 00000011111100000111111100000000 26 | 00000011111111111111111000000000 27 | 00000001111111111111110000000000 28 | 00000000111111111111110000000000 29 | 00000000111111111111100000000000 30 | 00000000011111111111000000000000 31 | 00000000111111111100000000000000 32 | 00000000001111110000000000000000 33 | -------------------------------------------------------------------------------- /classification/knn/testDigits/0_17.txt: -------------------------------------------------------------------------------- 1 | 00000000000001100000000000000000 2 | 00000000000111110111000000000000 3 | 00000000001111111111100000000000 4 | 00000000011111111111110000000000 5 | 00000000011111111111111000000000 6 | 00000000111111011111111000000000 7 | 00000000111110011111111100000000 8 | 00000001111100011111111100000000 9 | 00000001111100000000111110000000 10 | 00000011111000000000011110000000 11 | 00000001111100000000001111000000 12 | 00000001111000000000001111000000 13 | 00000001111000000000001111000000 14 | 00000011111000000000001111000000 15 | 00000011111000000000001111000000 16 | 00000011110000000000001111000000 17 | 00000011110000000000001111000000 18 | 00000011110000000000011111000000 19 | 00000011110000000000011111000000 20 | 00000011110000000000111111000000 21 | 00000011110000000000111110000000 22 | 00000011110000000000111100000000 23 | 00000011110000000011111100000000 24 | 00000001111000000011111110000000 25 | 00000000111100000111111100000000 26 | 00000000111111111111111000000000 27 | 00000000111111111111111000000000 28 | 00000000111111111111110000000000 29 | 00000000011111111111100000000000 30 | 00000000001111111111000000000000 31 | 00000000000111111100000000000000 32 | 00000000000011111000000000000000 33 | -------------------------------------------------------------------------------- /classification/knn/testDigits/0_18.txt: -------------------------------------------------------------------------------- 1 | 00000000000000011100000000000000 2 | 00000000000001111100000000000000 3 | 00000000000001111100000000000000 4 | 00000000000001111111000000000000 5 | 00000000000000111111000000000000 6 | 00000000110000001111000000000000 7 | 00000000111000000011110000000000 8 | 00000001111000000011110000000000 9 | 00000011111000000011110000000000 10 | 00000001111110000000111000000000 11 | 00000011111100000000111100000000 12 | 00000011111000000000111000000000 13 | 00000011111000000000011100000000 14 | 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