An Introduction to Statistical Learning

Book Title: An Introduction to Statistical Learning with Applications in R Authors: Gareth James, Daniela Witten, Trevor Hastie, Robert Tibshirani

Examples, excercises and comments made while reading the book. Coding in R using RStudio

Name		Name	Last commit message	Last commit date
Latest commit History 2 Commits
.RData		.RData
.Rhistory		.Rhistory
Auto.data		Auto.data
R-01 LoadingData - Plots - Linear Reg .R		R-01 LoadingData - Plots - Linear Reg .R
R-02 LogisticReg, LDA, QDA, KNN.R		R-02 LogisticReg, LDA, QDA, KNN.R
R-03 Cross Validation, K-Fold, LOOCV .R		R-03 Cross Validation, K-Fold, LOOCV .R
R-04 Subset Selection Methods - Forward - Backward Stepwise - Regularization.R		R-04 Subset Selection Methods - Forward - Backward Stepwise - Regularization.R
R-05 Trees.R		R-05 Trees.R
R-06 Bagging RandomForest.R		R-06 Bagging RandomForest.R
R-07 PCA - K.Means - Hierarchical Clustering.R		R-07 PCA - K.Means - Hierarchical Clustering.R
README.md		README.md

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