An Introduction to Statistical Learning: with Applications in R

Preface.- 1 Introduction.- 2 Statistical Learning.- 3 Linear Regression.- 4 Classification.- 5 Resampling Methods.- 6 Linear Model Selection and Regularization.- 7 Moving Beyond Linearity.- 8 Tree-Based Methods.- 9 Support Vector Machines.- 10 Deep Learning.- 11 Survival Analysis and Censored Data.- 12 Unsupervised Learning.- 13 Multiple Testing.- Index.

Binding Type: Paperback
Author: James, Gareth
Published: 08/13/2022
Publisher: Springer
ISBN: 9781071614204
Pages: 624
Weight: 1.90lbs
Size: 9.21h x 6.14w x 1.26d