The-Elements-Of-Statistical-Learning

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The-Elements-Of-Statistical-Learning

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This repository contains R code for exercices and plots in the famous book.

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# The-Elements-Of-Statistical-Learning
# All the work is dedicated to the book writers from whom I learned a great deal: Mr. Robert Tibshirani, Mr. Trevor Hastie, Mr. Jerome Friedman

This repository contains R code for exercices and plots in the famous book.
Repositories follow the book progression by chapter

# I. Libraries used:
Some libraries are written by me and used such as  
-lm2: linear models (pls, OLS, ridge, lasso, ...)  
-lc: linear classificatio  models (RRDA, LDA, QDA, ...)  
-ESLMixtures: mixtures described in the book  
-deepNets: deep neural network implementation  
-tree2:decision tree library  
-gbm2:gbm library  
For these libraries, .tar.gz source is uploaded in the /libs repository.  
Library can be installed and used simply by downloading the source code and executing r command:  
install.packages("package/URL",repos = NULL, type="source")  
Please feel free to check implementation of each library in the /modelsImplementation repository

# II. Numbering rules:
For any given chapter, files are entitled using the following code:  
typeNumber_ContentDescription.R Example: fig2_RidgeCoefficientProfile.R

# III. Work progress & contact:
I'm uploading the chapters one by one, please excuse me if you didn't find the chapter you're looking for, be sure it's on the way!  
If you have any suggestions regarding other figures/exercices or even another book, please let me know.  
email: <azzouz.marouen@gmail.com>

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