The Elements of Statistical Learning pdf epub mobi txt 电子书 下载 2025


The Elements of Statistical Learning

简体网页||繁体网页
T. Hastie
Springer
2003-07-30
520
USD 89.95
Hardcover
9780387952840

图书标签: 机器学习  统计学习  数据挖掘  统计学  Statistics  数学  Learning  Data-Mining   


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发表于2025-02-22

The Elements of Statistical Learning epub 下载 mobi 下载 pdf 下载 txt 电子书 下载 2025

The Elements of Statistical Learning epub 下载 mobi 下载 pdf 下载 txt 电子书 下载 2025

The Elements of Statistical Learning pdf epub mobi txt 电子书 下载 2025



图书描述

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 下载 mobi epub pdf txt 电子书

著者简介

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.


图书目录


The Elements of Statistical Learning pdf epub mobi txt 电子书 下载
想要找书就要到 小哈图书下载中心
立刻按 ctrl+D收藏本页
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用户评价

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1. 一点都不基础 被虐惨了 2. 新手千万不要看 3. 得读好几遍 = =

评分

多读几遍再评论

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对象看书引发我的猎奇心理 看了很闹心

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对于machine learning 零基础的人来说,太过生涩了。进阶读物,新手慎入

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只能算断断续续地读了其中一些吧

读后感

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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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这个简单的书评只是我个人的观点,所以我觉得先了解一下我的背景是有帮助的:本科计算机,数学功底尚可,研究生方向机器学习、数据挖掘相关应用研究。 缺点: 1,阅读此书前,读者需要具备基本的统计学知识,所以书的内容并不“基础”。 2,书中很少涉及到公式推导,细节并不...  

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http://www-stat.stanford.edu/~hastie/local.ftp/Springer/ESLII_print3.pdf  

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douban评论非要给出评价才能发表,这非常难决断 说你好呢,翻译的乱七八糟 说你不好呢,内容实在深刻 说起翻译来,这可是把中文说的比外文还难懂 Jiawei Han的数据挖掘让范明译的污七八糟 结果还让他来翻译这部经典,怀疑他在用google翻译 最后还是忍不住去图书馆复印了原版...  

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