An Introduction to Statistical Learning with Applications in R Springer Texts in Statistics
- This book presents some of the most important modeling and prediction techniques, along with relevant applications.
- Topics include linear regression, classification, re-sampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering,....
- Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science, industry, and other....
