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 co-developed much of the statistical modeling software and environment in R/S-PLUS and invented principal curves and surf...
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 co-developed much of the statistical modeling software and environment in R/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, projection pursuit and gradient boosting.
LAR uses least squares directions in the active set of variables.
Lasso uses least square directions; if a variable crosses zero, it is removed from the active set.
Boosting uses non-negative least squares directions in the active set. (查看原文)
Elements of statistic learning is one of the most important textbooks on algorithm analysis in the field of machine learning. The authors of this book, Trevor Hastie, Robert Tibshirani and Jerome Friedman, are pioneers in the area and have done really b...
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Chen_1st
Springer2016版
Dr. Who
Springer2016版
Kord
世界图书出版公司2009版
王飞
Springer2003版
doubling
1 有用 蝉 2014-03-30 15:46:30
: C8/6344
0 有用 M·贺六浑 2021-07-13 16:01:40
太美式了，乱哄哄的，没章法
0 有用 HauHwa Jau 2010-08-20 11:48:47
这书可读性很差，英文版也好不到哪里去
0 有用 diliwang 2013-10-12 12:51:20
大家都说不错，不过不是统计人，看得不清不楚
1 有用 迪云 2010-06-10 15:16:52
有点难...不是很好读.