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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
数据挖掘
机器学习
统计分析
数据库
人工智能
模式识别
商业智能
预测分析
聚类分析
分类算法

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具体描述

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.