├── .gitignore ├── Boosting.R ├── BoostingDoc.Rmd ├── Bootstrapping.R ├── DecisionTrees.R ├── DiscriminantAnalysis.R ├── GAM.Rmd ├── GeneralizedAdditiveModels.R ├── K-MEANS.Rmd ├── K-NN.R ├── LogisticRegression.R ├── Model Selection Techinques.R ├── NonLinearModel.Rmd ├── NonLinearModel.pdf ├── NonLinearModels.R ├── Notes ├── LINEAR REGRESSION.docx └── Models.docx ├── PCA-notebook.rmd ├── PCA.R ├── Plots ├── 10 fold CV for Model Selection in Forward Stepwise.png ├── 10 foldcverror.png ├── 5 fold vs 10 fold CV error.png ├── Backward stepwise Selection.png ├── Forward Stepwise Selection.png ├── LOOCV.errors.png ├── Lasso-Cross Validaation and Model Selection.png ├── Lasso-Validation Set Implementation.png ├── Model Selection Best Subset Cp statistic.png ├── Number of variables vs Cp and Adjs R2.png ├── PRINCIPAL_COMPONENTSPLOT.png ├── Quality of Model statistics plot.png ├── RMS error on TRAIN vs TEST.png ├── Ridge Regression.png ├── bootstrapOutput.png └── lasso-Fraction of Deviance explained.png ├── README.md ├── RadialKernelSVM.R ├── RadialKernelSVMnotebook.Rmd ├── RandomForestEnsemble.Rmd ├── RandomForests.R ├── Regression.R ├── Ridge Regression and Lasso-Regularization Techniques.R ├── SVMNotebook.Rmd ├── Splines.R ├── Splines.Rmd ├── TreeBasedTechniques.Rmd ├── crossValidation.R └── svm.R /.gitignore: -------------------------------------------------------------------------------- 1 | .RData 2 | .Rhistory 3 | *.html 4 | rsconnect/* 5 | -------------------------------------------------------------------------------- /Boosting.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/anishsingh20/Statistical-Learning-using-R/HEAD/Boosting.R -------------------------------------------------------------------------------- /BoostingDoc.Rmd: -------------------------------------------------------------------------------- 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