The Elements of Statistical Learning pdf epub mobi txt 电子书 下载 2024


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2024-12-22

The Elements of Statistical Learning epub 下载 mobi 下载 pdf 下载 txt 电子书 下载 2024

The Elements of Statistical Learning epub 下载 mobi 下载 pdf 下载 txt 电子书 下载 2024

The Elements of Statistical Learning pdf epub mobi txt 电子书 下载 2024



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
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用户评价

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对于每种方法高屋建瓴的介绍很有启发性

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只能算断断续续地读了其中一些吧

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半年攻下!

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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 = =

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半年攻下!

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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