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1.

電子ブック
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1. The Elements of Statistical Learning : Data Mining, Inference, and Prediction
by Jerome Friedman, Robert Tibshirani, Trevor Hastie
出版情報: New York, NY : Springer-Verlag New York, 2009
シリーズ名: Springer Series in Statistics ;
オンライン: http://dx.doi.org/10.1007/b94608
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2.

電子ブック
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2. An Introduction to Statistical Learning : with Applications in R
by Gareth James, Daniela Witten, Trevor Hastie, Robert Tibshirani
出版情報: New York, NY : Springer New York : Imprint: Springer, 2013
シリーズ名: Springer Texts in Statistics ; 103
オンライン: http://dx.doi.org/10.1007/978-1-4614-7138-7
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目次情報: 続きを見る
Introduction
Statistical Learning
Linear Regression
Classification
Resampling Methods
Linear Model Selection and Regularization
Moving Beyond Linearity
Tree-Based Methods
Support Vector Machines
Unsupervised Learning
Index
Introduction
Statistical Learning
Linear Regression
3.

電子ブック
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3. An Introduction to Statistical Learning : with Applications in R. 2nd ed. 2021
by Gareth James, Daniela Witten, Trevor Hastie, Robert Tibshirani
出版情報: New York, NY : Springer US : Imprint: Springer, 2021
シリーズ名: Springer Texts in Statistics ;
オンライン: https://doi.org/10.1007/978-1-0716-1418-1
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目次情報: 続きを見る
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
Preface
1 Introduction
2 Statistical Learning