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.
具体描述
读后感
作者不是Jiawei Han好嘛. 没读过写什么书评! 作者是怀卡托大学的Ian和Eibe, Weka的发明人. 没看过别瞎BB. 豆瓣写错author你们就顺杆爬有意思么...............................................................................................................................
评分这本dm的书啃完了，觉得有点这个书有点“偏见”，怎么理解呢 前面的东西不错哦，可是后半部分的Weka平台我个人觉得翻翻就行了，要学还不如看看spss的书呢，前面关于机器模型的建立的数学基础要求的不是很高，所以很适合一般没有学过随机过程的人看看，要是数学很牛的人，可以看...
评分----------------------------------------- 外文教材， 外文参考书 请咨询 http://shop35575714.taobao.com ----------------------------------------
评分这种书的翻译都是一个导师，找多个研究生每人分俩章节，对这金山词霸翻译的，能好到哪里。所以要读还是读原版。
评分这种书的翻译都是一个导师，找多个研究生每人分俩章节，对这金山词霸翻译的，能好到哪里。所以要读还是读原版。
用户评价
指定教科书，比较实际，讲weka的
评分应该更早读的
评分应该更早读的
评分我再次选择了撤离，转向RapidMiner
评分应该更早读的
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