The Elements Of Statistical Learning. Data Mining, Inference, And Prediction - Couverture rigide

Hastie, Trevor; Tibshirani, Robert; Friedman, Jerome

 
9780387952840: The Elements Of Statistical Learning. Data Mining, Inference, And Prediction
Couverture rigide
ISBN 10 : 0387952845 ISBN 13 : 9780387952840
Editeur : Springer-Verlag New York Inc., 2003

Synopsis

During the past decade, there has been an explosion in computation and information technology. With it has come vast amounts 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 different terminology. This book describes the important ideas in these areas in common conceptual framework. While the approach is statistical, the emphasis on concepts rather than mathematics. Many examples are given with a liberal use of color graphics. It should be a valuable resource for statisticians and anyone interested in data mining in science or industry. The book's coverage is broad, from supervised learning (prediction) to unsupervised learning. The many topics include neural networks, support machines, classification trees, and boosting - the first comprehensive treatment of this topic in any book.

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À propos de l?auteur

Trevor Hastie, Robert Tibshirani, and Jerome Friedman are professors of statistics at Stanford University and prominent researchers in this area. Hastie and Tibshirani developed generalized additive models and wrote a popular book of that title. Hastie wrote much of the statistical modeling software in S-PLUS and invented principal curves and surfaces. Tibshirani proposed the Lasso and is co-author of the very successful An Introduction to the Bootstrap. Friedman is the co-inventor of many data-mining tools including CART, MARS, and projection pursuit.

Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.

Éditeur
Springer-Verlag New York Inc.
Date d'édition
2003
Langue
anglais
ISBN 10 
0387952845
ISBN 13 
9780387952840
Reliure
Relié
Nombre de pages
552
Coordonnées du fabricant
non disponible
Personne responsable
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