【文件属性】：
文件名称：The Elements of Statistical Learning
文件大小：13.16MB
文件格式：PDF
更新时间：2022-03-29 07:49:57
statis deep l
the second edition
chapter:
1. Introduction
2. Overview of Supervised Learning 3. Linear Methods for Regression
4. Linear Methods for Classification 5. Basis Expansions and Regulariza- tion
6. Kernel Smoothing Methods
7. Model Assessment and Selection
8. Model Inference and Averaging 9. Additive Models, Trees, and Related Methods
10. Boosting and Additive Trees
11. Neural Networks
12. Support Vector Machines and Flexible Discriminants
13. Prototype Methods Nearest-Neighbors
14. Unsupervised Learning
15. Random Forests
16. Ensemble Learning
17. Undirected Graphical Models
18. High-Dimensional Problems