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THE ELEMENTS OF STATISTICAL LEARNING: DATA MINING, INFERENCE, AND PREDICTION

by Trevor Hastie; Robert J. Tibshirani; Jerome Friedman

Published by Springer. Circa. 2001

Very good condition. Springer Series in Statistics. Data mininbg, machine learning, and bioinformatics. This book describes the important ideas in these areas in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics. Many examples are given with a liberal use of color graphics. Matt yellow and brown boards. xvi and 533 pages including index.

Spine slightly faded. Corners bumped. Old price label to rear board. A few marks and corner creases to contents.

ISBN: 0387952845
Stock no. 1821056

Sorry this book has been sold (20/04/2021)
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Contents

  • Preface
  • 1 Introduction
  • 2 Overview of Supervised Learning
  • 3 Linear Methods for Regression
  • 4 Linear Methods for Classification
  • 5 Basis Expansions and Regularization
  • 6 Kernel Methods
  • 7 Model Assessment and Selection
  • 8 Model Inference and Averaging
  • 9 Additive Models, Trees and Related Methods
  • 10 Boosting and Additive Trees
  • 11 Neural Networks
  • 12 Support Vector Machines and Flexible Discriminants
  • 13 Prototype Methods and Nearest-Neighbours
  • 14 Unsupervised Learning
  • References
  • Author Index
  • Index

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