The Elements of Statistical Learning pdf epub mobi txt 電子書 下載 2024


The Elements of Statistical Learning

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T. Hastie
Springer
2003-07-30
520
USD 89.95
Hardcover
9780387952840

圖書標籤: 機器學習  統計學習  數據挖掘  統計學  Statistics  數學  Learning  Data-Mining   


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发表于2024-12-22

The Elements of Statistical Learning epub 下載 mobi 下載 pdf 下載 txt 電子書 下載 2024

The Elements of Statistical Learning epub 下載 mobi 下載 pdf 下載 txt 電子書 下載 2024

The Elements of Statistical Learning pdf epub mobi txt 電子書 下載 2024



圖書描述

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.

The Elements of Statistical Learning 下載 mobi epub pdf txt 電子書

著者簡介

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.


圖書目錄


The Elements of Statistical Learning pdf epub mobi txt 電子書 下載
想要找書就要到 小哈圖書下載中心
立刻按 ctrl+D收藏本頁
你會得到大驚喜!!

用戶評價

評分

typo太多瞭,勘誤居然有100多頁。不要買first printing。

評分

對象看書引發我的獵奇心理 看瞭很鬧心

評分

瀏覽過,經典之作

評分

隻能算斷斷續續地讀瞭其中一些吧

評分

感覺比PRML更清晰

讀後感

評分

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...  

評分

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...  

評分

我导师(stanford博士毕业)非常欣赏这本书,并把它作为我博士资格考试的参考教材之一。 感谢 ZHENHUI LI 提供的信息。本书作者已经将第二版的电子书放到网上,大家可以免费下载。 http://www-stat.stanford.edu/~tibs/ElemStatLearn/ 网上还有一份solution manual, 但是似乎...  

評分

对于新手来说,这本书和PRML比起来差太远,新手强烈建议去读PRML,接下来再看这本书。。我就举个最简单的例子吧,这本书的第二章overview of supervised learning和PRML的introduction差太远了。。。。读这本书的overview如果读者没有基础几乎不知所云。。但是PRML通过一个例子...  

評分

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.

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