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


The Elements of Statistical Learning

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T. Hastie 作者
Springer
譯者
2003-07-30 出版日期
520 頁數
USD 89.95 價格
Hardcover
叢書系列
9780387952840 圖書編碼

The Elements of Statistical Learning 在線電子書 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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發表於2024-06-02

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

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

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



The Elements of Statistical Learning 在線電子書 用戶評價

評分

半年攻下!

評分

最近在看,mark一下

評分

對象看書引發我的獵奇心理 看瞭很鬧心

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Amazon上麵能夠看到第二版的信息瞭,但是不知道相應的電子書哪年纔能等到。去年老師總是對我說,這本書很難很難...就決定拿它來祭旗吧

評分

typo太多瞭,勘誤居然有100多頁。不要買first printing。

The Elements of Statistical Learning 在線電子書 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.


The Elements of Statistical Learning 在線電子書 著者簡介


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

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


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立刻按 ctrl+D收藏本頁
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The Elements of Statistical Learning 在線電子書 讀後感

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...  

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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.

評分

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...  

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