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the elements of statistical learning-----data mining,inference,and prediction by Trevor Hastie, Robert Tibshirani Jerome Friedman

Bayesian data analysis by Andrew Gelman, John B. Carlin. Hal S. Stem and Donald B. Rubin

能否分享一下啊？谢谢了！

[此贴子已经被作者于2006-12-20 4:39:31编辑过]

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关键词：统计学 Statistical Data Mining Tibshirani Prediction 统计学

每人帮忙啊，自己顶一下！

The elements of statistical learning :Data Mining, Inference, and Prediction

我有这本电子书,但是是djvu格式.

另我发帖的Handbook Of Data Mining也很值得参考

https://bbs.pinggu.org/thread-116844-1-1.html

The Elements of Statistical Learning

ISBN: 0387952845
Author: T. Hastie / R. Tibshirani / J. H. Friedman
Publisher: Springer
URL: /http://www.amazon.com/exec/obidos/redirect?tag=songstech-20&path=ASIN%2F0387952845
Summary:
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 with different terminology. This book descibes theimprtant ideas in these areas ina 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. It should be a vluable resource for statisticians and anyone interested in data mining in science or industry. The book's coverage is broad, from supervised learing (prediction) to unsupervised learning. The many topics include neural networks, support vector machines, classification trees and boosting--the first comprehensive treatment of this topic in any book. Trevor Hastie, Robert Tibshirani, and Jerome Friedman are professors of statistics at Stanford University. They are 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.
http://16.mihd.net/dl/aaabb72b10e92f87652b684b65e931dc/458a9786/16-ay7bjc-480602/0387952845.djvu

以下是引用DreadNight在2006-12-21 22:19:00的发言：

The Elements of Statistical Learning

ISBN: 0387952845
Author: T. Hastie / R. Tibshirani / J. H. Friedman
Publisher: Springer
URL: /http://www.amazon.com/exec/obidos/redirect?tag=songstech-20&path=ASIN%2F0387952845
Summary:
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 with different terminology. This book descibes theimprtant ideas in these areas ina 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. It should be a vluable resource for statisticians and anyone interested in data mining in science or industry. The book's coverage is broad, from supervised learing (prediction) to unsupervised learning. The many topics include neural networks, support vector machines, classification trees and boosting--the first comprehensive treatment of this topic in any book. Trevor Hastie, Robert Tibshirani, and Jerome Friedman are professors of statistics at Stanford University. They are 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.
http://16.mihd.net/dl/aaabb72b10e92f87652b684b65e931dc/458a9786/16-ay7bjc-480602/0387952845.djvu