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

Written by Trevor Hastie, Robert J. Tibshirani, Jerome Friedman
Published by Springer in 2001
ISBN: 0387952845

£ 35.00 Photo of THE ELEMENTS OF STATISTICAL LEARNING: DATA MINING, INFERENCE, AND PREDICTION- Stock Number: 1830310

THE ELEMENTS OF STATISTICAL LEARNING: DATA MINING, INFERENCE, AND PREDICTION
Written by Trevor Hastie, Robert J. Tibshirani, Jerome Friedman.
Stock no. 1830310
2002. Hardback. 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. ISBN: 0387952845. 2nd printing. Boards lightly scuffed and marked. Text block a little grubby. Name in ink to top edge of front endpaper. Contents clean.

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Front cover

Cover of THE ELEMENTS OF STATISTICAL LEARNING: DATA MINING, INFERENCE, AND PREDICTION by Trevor Hastie; Robert J. Tibshirani; Jerome Friedman

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