pqhieu/islr2

Exercise solutions for "An Introduction to Statistical Learning"

Introduction to Statistical Learning

Exercise solutions for "Introduction to Statistical Learning with Applications in R, 2nd edition", written in R using org mode.

Solutions

Chapter 5

• Lab
  • The validation set approach
  • Leave-one-out cross-validation
  • k-fold cross-validation
  • The bootstrap
• Exercises
  • Exercise 1
  • Exercise 2
  • Exercise 3
  • Exercise 4
  • Exercise 5
  • Exercise 6
  • Exercise 7
  • Exercise 8
  • Exercise 9

Chapter 6

• Lab
  • Subset selection methods
  • Ridge regression and the lasso
  • PCR and PLS regression
• Exercises
  • Exercise 1
  • Exercise 2
  • Exercise 3
  • Exercise 4
  • Exercise 5
  • Exercise 6
  • Exercise 7
  • Exercise 8
  • Exercise 9
  • Exercise 10
  • Exercise 11

Chapter 7

• Lab
  • Polynomial regression and step functions
  • Splines
  • GAMs
• Exercises
  • Exercise 1
  • Exercise 2
  • Exercise 3
  • Exercise 4
  • Exercise 5
  • Exercise 6
  • Exercise 7
  • Exercise 8
  • Exercise 9
  • Exercise 10
  • Exercise 11
  • Exercise 12

Chapter 8

• Lab
  • Fitting classification trees
  • Fitting regression trees
  • Bagging and random forests
  • Boosting
  • Bayesian additive regression trees
• Exercises
  • Exercise 1
  • Exercise 2
  • Exercise 3
  • Exercise 4
  • Exercise 5
  • Exercise 6
  • Exercise 7
  • Exercise 8
  • Exercise 9
  • Exercise 10
  • Exercise 11
  • Exercise 12