The Elements of Statistical Learning pdf epub mobi txt 电子书 下载 2025
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.
- 机器学习
- 统计学习
- 数据挖掘
- 统计学
- Statistics
- 数学
- Learning
- Data-Mining
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 the important ideas in these areas in a 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 valuable 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 <EM>An Introduction to the Bootstrap</EM>. Friedman is the co-inventor of many data-mining tools including CART, MARS, and projection pursuit.
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读后感
非常难，一点都不element，是本百科全书式的读物，如果是初学者，不建议读 很多章节也没有细节，概述性的东西，能看懂几章就很不错了 其实每章都可以写成一本书，都可以做很多篇的论文 全部读懂非常非常难，倒是作为用到哪个部分作为参考资料查查很不错
评分英文原版的官方免费下载链接已经有人在书评中给出了 中文版的译者很可能没有基本的数学知识，而是用Google翻译完成了这部作品。 超平面的Normal equation （法线方程）翻译成了“平面上的标准方程”；而稍有高中髙维几何常识的人都知道，法线是正交与该超平面的方向，而绝不可...
评分统计学习的经典教材，数学难度适中，英文难度较低，看了其中有监督学习部分，无监督学习部分没怎么看，算法比较经典，但是也比较老。
评分统计学习的经典教材，数学难度适中，英文难度较低，看了其中有监督学习部分，无监督学习部分没怎么看，算法比较经典，但是也比较老。
用户评价
so clear and comprehensive
评分对象看书引发我的猎奇心理 看了很闹心
评分被称为工具书之神，被虐惨了，完全搞不懂
评分半年攻下！
评分内容很多，读起来不是很容易 对于进入这个领域的人来说作为第一本打基础的书很不错
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