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Table of Contents
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.

An Introduction to Statistical Learning

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    Order before 4pm today for delivery by Tue 30 Jun 2026.

    A Paperback / softback by Gareth James, Daniela Witten, Trevor Hastie

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      Publisher: Springer-Verlag New York Inc.
      Publication Date: 30/07/2022
      ISBN13: 9781071614204, 978-1071614204
      ISBN10: 1071614207
      Also in:
      Non Fiction Computing Artificial intelligence (AI) Mathematical and statistical software Mathematics Probability and statistics

      Description

      Book Synopsis


      Table of Contents
      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.

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