Data Mining

Data Mining pdf epub mobi txt 电子书 下载 2025

出版者:Morgan Kaufmann
作者:Ian H. Witten
出品人:
页数:560
译者:
出版时间:2005-6-22
价格:USD 75.95
装帧:Paperback
isbn号码:9780120884070
丛书系列:
图书标签:
  • 数据挖掘 
  • 机器学习 
  • DataMining 
  • 计算机 
  • 数据库 
  • 计算机科学 
  • 人工智能 
  • Data-Mining 
  •  
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As with any burgeoning technology that enjoys commercial attention, the use of data mining is surrounded by a great deal of hype. Exaggerated reports tell of secrets that can be uncovered by setting algorithms loose on oceans of data. But there is no magic in machine learning, no hidden power, no alchemy. Instead there is an identifiable body of practical techniques that can extract useful information from raw data. This book describes these techniques and shows how they work. The book is a major revision of the first edition that appeared in 1999. While the basic core remains the same, it has been updated to reflect the changes that have taken place over five years, and now has nearly double the references. The highlights for the new edition include thirty new technique sections; an enhanced Weka machine learning workbench, which now features an interactive interface; comprehensive information on neural networks; a new section on Bayesian networks; plus much more; algorithmic methods at the heart of successful data mining-including tried and true techniques as well as leading edge methods; performance improvement techniques that work by transforming the input or output; and, downloadable Weka, a collection of machine learning algorithms for data mining tasks, including tools for data pre-processing, classification, regression, clustering, association rules, and visualization-in a new, interactive interface.

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作者可以说是享誉盛名,但是这本书写出来,基本上章法全无。理论和例子基本上没有几个是适合入门者的,加上翻译有些地方表意不清。初阶入门者看了的话,肯定一团迷雾。 评论太短了嘛?评论太短了嘛?评论太短了嘛?评论太短了嘛?评论太短了嘛?评论太短了嘛?评论太短了嘛?评...

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国内教科书都是先进来源、历史、分类、发展、趋势等。外国人写的上来稍微介绍一下就像专业知识进军啦  

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----------------------------------------- 外文教材, 外文参考书 请咨询 http://shop35575714.taobao.com ----------------------------------------  

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一会是查询偏差,一会是搜索偏差~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~  

用户评价

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应该更早读的

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我再次选择了撤离,转向RapidMiner

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关于机器学习

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sdfsdfsdf

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应该更早读的

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