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Academic & Professional Books  Reference  Data Analysis & Modelling  Data Analysis & Statistics

The Elements of Statistical Learning Data Mining, Inference, and Prediction

Out of Print
By: Trevor Hastie, Robert Tibshirani and Jerome Friedman
549 pages, 200 illus. in color.
Publisher: Springer Nature
The Elements of Statistical Learning
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  • The Elements of Statistical Learning ISBN: 9780387952840 Edition: 3 Hardback Dec 2001 Out of Print #174222
About this book Contents Related titles

About this book

During the past decade there has been an explosion in computation and information technology. With it has come a vast amount of data in a variety of fields such as medicine, biology, finance, and marketing. The challenge of understanding these data has led to the development of new tools in the field of statistics, and spawned new areas such as data mining, machine learning, and bioinformatics. Many of these tools have common underpinnings but are often expressed with different terminology. 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.

Contents

Overview of Supervised Learning.- Linear Methods for Regression.- Linear Methods for Classification.- Basic Expansions and Regularization.- Kernel Methods.- Model Assessment and Selection.- Model Inference and Averaging.- Additive Models, Trees, and Related Methods.- Boosting and Additive Trees.- Neural Networks.- Support Vector Machines and Flexible Discriminates.- Prototype Methods and Nearest Neighbors.- Unsupervised Learning.

Customer Reviews

Out of Print
By: Trevor Hastie, Robert Tibshirani and Jerome Friedman
549 pages, 200 illus. in color.
Publisher: Springer Nature
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