阅读推荐 |《The Elements of Statistical Learning》pdf_下载

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阅读推荐 |《The Elements of Statistical Learning》pdf_下载

作者: T. Hastie / R. Tibshirani / J. H.Friedman
出版年: 2003-07-30

内容简介

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During the past decade there has been an explosion in computationand information technology. With it has come vast amounts of data in a varietyof fields such as medicine, biology, finance, and marketing. The challenge ofunderstanding these data has led to the development of new tools in the fieldof statistics, and spawned new areas such as data mining, machine learning, andbioinformatics. Many of these tools have common underpinnings but are oftenexpressed with different terminology. This book descibes the important ideas inthese areas in a common conceptual framework. While the approach isstatistical, the emphasis is on concepts rather than mathematics. Many examplesare given, with a liberal use of color graphics. It should be a valuableresource for statisticians and anyone interested in data mining in science orindustry. The book's coverage is broad, from supervised learing (prediction) tounsupervised learning. The many topics include neural networks, support vectormachines, classification trees and boosting--the first comprehensive treatmentof this topic in any book. Trevor Hastie, Robert Tibshirani, and JeromeFriedman are professors of statistics at Stanford University. They areprominent researchers in this area: Hastie and Tibshirani developed generalizedadditive models and wrote a popular book of that title. Hastie wrote much ofthe statistical modeling software in S-PLUS and invented principal curves andsurfaces. Tibshirani proposed the Lasso and is co-author of the very successful<EM>An Introduction to the Bootstrap</EM>. Friedman is theco-inventor of many data-mining tools including CART, MARS, and projectionpursuit.

作者简介

——————————

Trevor Hastie, Robert Tibshirani, andJerome Friedman are professors of statistics at Stanford University. They areprominent researchers in this area: Hastie and Tibshirani developed generalizedadditive models and wrote a popular book of that title. Hastie co-developedmuch of the statistical modeling software and environment in R/S-PLUS andinvented principal curves and surfaces. Tibshirani proposed the lasso and isco-author of the very successful An Introduction to the Bootstrap. Friedman isthe co-inventor of many data-mining tools including CART, MARS, projectionpursuit and gradient boosting.

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• The_Elements_of_Statistical_Learning_.pdf

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