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Statistical Learning

Repository of R code for all lab exercises in the book "An Introduction to Statistical Learning"

The Stanford Online course, by T. Hastie and R. Tibshirani, was completed on April, 2015.

Index:

  1. Ch.2 (p.42-51) INTRODUCTION TO R
  2. Ch.3 (p.109-119) LINEAR REGRESSION
  3. Ch.4 (p.154-167) CLASSIFICATION: Logistic Regression, LDA, QDA, and KNN
  4. Ch.5 (p.190-197) RESAMPLING METHODS: Cross-Validation and Bootstrap
  5. Ch.6 (p.244-259) LINEAR MODEL SELECTION AND REGULARIZATION (Lasso and Ridge)
  6. Ch.7 (p.287-297) BEYOND LINEARITY: Polynomial Regression, Step Functions, Splines, GAM's
  7. Ch.8 (p.324-331) TREE-BASED METHODS: Bagging, Random Forests, Boosting
  8. Ch.9 (p.359-368) SUPPORT VECTOR MACHINES
  9. Ch.10 (p.401-413) UNSUPERVISED LEARNING: PCA and Clustering (K-Means, Hierarchical)

Datasets used in the lab exercises (p.14 of the book):

Auto: Gas mileage, horsepower, and other information for cars.
Boston: Housing values and other information about Boston suburbs.
Caravan: Information about individuals offered caravan insurance.
Carseats: Information about car seat sales in 400 stores.
College: Demographic characteristics, tuition, and more for USA colleges.
Default: Customer default records for a credit card company.
Hitters: Records and salaries for baseball players.
Khan: Gene expression measurements for four cancer types.
NCI60: Gene expression measurements for 64 cancer cell lines.
OJ: Sales information for Citrus Hill and Minute Maid orange juice.
Portfolio: Past values of financial assets, for use in portfolio allocation.
Smarket: Daily percentage returns for S&P 500 over a 5-year period.
USArrests: Crime statistics per 100,000 residents in 50 states of USA.
Wage: Income survey data for males in central Atlantic region of USA.
Weekly: 1,089 weekly stock market returns for 21 years.

All data sets are available in the ISLR library, with the exception of Boston (part of MASS) and USArrests (part of the base R distribution).

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Repository of R code for all lab exercises in the book "An Introduction to Statistical Learning"

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