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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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