文档介绍：To our parents:
Valerie and Patrick Hastie
Vera and Sami Tibshirani
Florence and Harry Friedman
and to our families:
Samantha, Timothy, and Lynda
Charlie, Ryan, Julie, and Cheryl
Melanie, Dora, Monika, and Ildiko
vi
Preface to the Second Edition
In God we trust, all others bring data.
–William Edwards Deming (1900-1993)1
We have been gratified by the popularity of the first edition of The
Elements of Statistical Learning. This, along with the fast pace of research
in the statistical learning field, motivated us to update our book with a
second edition.
We have added four new chapters and updated some of the existing
chapters. Because many readers are familiar with the layout of the first
edition, we have tried to change it as little as possible. Here is a summary
of the main changes:
1On the Web, this quote has been widely attributed to both Deming and Robert W.
Hayden; however Professor Hayden told us that he can claim no credit for this quote,
and ironically we could find no “data” confirming that Deming actually said this.
viii Preface to the Second Edition
Chapter What’s new
1. Introduction
2. Overview of Supervised Learning
3. Linear Methods for Regression LAR algorithm and generalizations
of the lasso
4. Linear Methods for Classification Lasso path for logistic regression
5. Basis Expansions and Regulariza- Additional illustrations of RKHS
tion
6. Kernel Smoothing Methods
7. Model Assessment and Selection Strengths and pitfalls of cross-
validation
8. Model Inference and Averaging
9. Additive Models, Trees, and
Related Methods
10. Boosting and Additive Trees New example from ecology; some
material split off to Chapter 16.
11. works Bayesian s and the NIPS
2003 challenge
12. Support Vector Machines and Path algorithm for SVM classifier
Flexible Discriminants
13. Prototype Methods and
Nearest-Neighbors
14. Unsupervised Learning Spectral clustering, kernel PCA,
sparse PCA, non-negative matri