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.
具体描述
读后感
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。
评分有人给我推荐这本书的时候说，有了这本书，就不再需要其他的机器学习教材了。 入手这本书的接下来两个月，我与教材中艰深的统计推断、矩阵、数值算法、凸优化等数学知识展开艰苦的斗争。于是我明白了何谓”不需要其他的机器学习教材“：准确地说，是其他的教材都不需要了；一本...
评分The methodology used in the books are fancy and attractive, yet in terms of rigorous proofs, sometimes the book skip steps and is difficult to follow. ~ Slightly sophisticated for undergraduate students, but in general is a very nice book.
评分个人觉得“机器学习 -- 从入门到精通”可以作为这本书的副标题。 机器学习、数据挖掘或者模式识别领域有几本非常流行的教材，比如Duda的模式分类，Bishop的PRML。Duda的书第一版是模式识别的奠基之作，现在大家谈论得是第二版，因为内容相对简单，非常流行，但对近20年取得统...
评分个人觉得“机器学习 -- 从入门到精通”可以作为这本书的副标题。 机器学习、数据挖掘或者模式识别领域有几本非常流行的教材，比如Duda的模式分类，Bishop的PRML。Duda的书第一版是模式识别的奠基之作，现在大家谈论得是第二版，因为内容相对简单，非常流行，但对近20年取得统...
用户评价
多读几遍再评论
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
评分so clear and comprehensive
评分被称为工具书之神，被虐惨了，完全搞不懂
评分只能算断断续续地读了其中一些吧
相关图书
本站所有内容均为互联网搜索引擎提供的公开搜索信息，本站不存储任何数据与内容，任何内容与数据均与本站无关，如有需要请联系相关搜索引擎包括但不限于百度，google,bing,sogou 等
© 2025 book.wenda123.org All Rights Reserved. 图书目录大全 版权所有