An Introduction to Statistical Learning: with Applications in R (Springer T…



An Introduction to Statistical Learning This book presents key modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, and clustering.