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书名：The Elements of Statistical Learning—Data Ming, Inference, and Prediction

作者：Trevor Hastie, Robert Tibshirani and Jerome Friedman

出版社：Springer，

文件格式：pdf

文件大小：47MB

简要目录：

Preface
1 Introduction………. 1
2 Overview of Supervised Learning……………. 9
3   Linear Methods for Regression 41
5  Basis Expansions and Regularization 115
6  Kernel Methods 165
7  Model Assessment and Selection 193
8  Model Inference and Averaging 225
9  Additive Models, Trees, and Related Methods 257
10  Boosting and Additive Trees 299
11  Neural Networks 347
12  Support Vector Machines and Flexible Discriminants 371
13  Prototype Methods and Nearest-Neighbors 411
14  Unsupervised Learning 437
Bibliographic Notes ......................... 503
Exercises ............................... 504
References 509
Author Index 523
Index 527

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