ISLR_Python

Figures, Tables and Problems from the book <A target="_blank" href='http://www-bcf.usc.edu/%7Egareth/ISL/index.html'>'An Introduction to Statistical Learning with Applications in R'</A> by James, Witten, Hastie, Tibshirani (2013). Using Python 3.x.

List of Chapters:

• [x] <A href='http://nbviewer.jupyter.org/github/pedvide/ISLR_Python/blob/master/Chapter3_Linear_regression.ipynb'>Chapter 3 - Linear Regression</A>
• [x] <A href='http://nbviewer.jupyter.org/github/pedvide/ISLR_Python/blob/master/Chapter4_classification.ipynb'>Chapter 4 - Classification</A>
• [x] <A href='http://nbviewer.jupyter.org/github/pedvide/ISLR_Python/blob/master/Chapter5_Resampling_Methods.ipynb'>Chapter 5 - Resampling Methods</A>
• [x] <A href='http://nbviewer.jupyter.org/github/pedvide/ISLR_Python/blob/master/Chapter6_Linear_Model_Selection_and_Regularization.ipynb'>Chapter 6 - Linear Model Selection and Regularization</A>
• [x] <A href='http://nbviewer.jupyter.org/github/pedvide/ISLR_Python/blob/master/Chapter7_Moving_Beyond_Linearity.ipynb'>Chapter 7 - Moving Beyond Linearity</A>
• [x] <A href='http://nbviewer.jupyter.org/github/pedvide/ISLR_Python/blob/master/Chapter8_Tree_Based_Methods.ipynb'>Chapter 8 - Tree-Based Methods</A>
• [x] <A href='http://nbviewer.jupyter.org/github/pedvide/ISLR_Python/blob/master/Chapter9_Support_Vector_Machines.ipynb'>Chapter 9 - Support Vector Machines</A>
• [x] <A href='http://nbviewer.jupyter.org/github/pedvide/ISLR_Python/blob/master/Chapter10_Unsupervised_Learning.ipynb'>Chapter 10 - Unsupervised Learning</A>

Dependencies:

• pandas
• numpy
• scipy
• scikit-learn
• statsmodels
• patsy
• matplotlib
• seaborn
• pyGAM
• pydot and graphviz (to plot decission trees)
• scikit-plot (to plot ROC for classification)

I obtained the data from https://github.com/JWarmenhoven/ISLR-python.

References:

James, G., Witten, D., Hastie, T., Tibshirani, R. (2013). <I>An Introduction to Statistical Learning with Applications in R</I>, Springer Science+Business Media, New York. http://www-bcf.usc.edu/~gareth/ISL/index.html

Hastie, T., Tibshirani, R., Friedman, J. (2009). <I>Elements of Statistical Learning</I>, Second Edition, Springer Science+Business Media, New York. https://web.stanford.edu/~hastie/ElemStatLearn/