Data Mining: Practical Machine Learning Tools and Techniques with Java ImplementationsThis book offers a thorough grounding in machine learning concepts as well as practical advice on applying machine learning tools and techniques in realworld data mining situations. Inside, you'll learn all you need to know about preparing inputs, interpreting outputs, evaluating results, and the algorithmic methods at the heart of successful data miningincluding both triedandtrue techniques of the past and Javabased methods at the leading edge of contemporary research. If you're involved at any level in the work of extracting usable knowledge from large collections of data, this clearly written and effectively illustrated book will prove an invaluable resource. Complementing the authors' instruction is a fully functional platformindependent Java software system for machine learning, available for download. Apply it to the sample data sets provided to refine your data mining skills, apply it to your own data to discern meaningful patterns and generate valuable insights, adapt it for your specialized data mining applications, or use it to develop your own machine learning schemes. * Helps you select appropriate approaches to particular problems and to compare and evaluate the results of different techniques. * Covers performance improvement techniques, including input preprocessing and combining output from different methods. * Comes with downloadable machine learning software: use it to master the techniques covered inside, apply it to your own projects, and/or customize it to meet special needs. 
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Review: Data Mining: Practical Machine Learning Tools and Techniques (Morgan Kaufmann Series in Data Management Systems)
User Review  Kid  GoodreadsBest introductory book on Data Mining in terms of concepts and practice. Not too academically but goaldriven and datadriven, which makes readers understand it easier. WEKA is a great tool, although ... Read full review
Review: Data Mining: Practical Machine Learning Tools and Techniques (Morgan Kaufmann Series in Data Management Systems)
User Review  GoodreadsBest introductory book on Data Mining in terms of concepts and practice. Not too academically but goaldriven and datadriven, which makes readers understand it easier. WEKA is a great tool, although ... Read full review
Contents
III  1 
V  2 
VI  4 
VII  5 
VIII  7 
IX  8 
XI  11 
XII  13 
CX  169 
CXII  170 
CXIII  171 
CXIV  172 
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CVI  162 
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CXC  294 
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CXCII  297 
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CXCV  306 
CXCVII  314 
CXCIX  316 
CC  317 
CCI  321 
CCIII  322 
CCIV  325 
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CCVII  329 
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CCX  333 
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Other editions  View all
Data Mining: Practical Machine Learning Tools and Techniques Ian H. Witten,Eibe Frank,Mark A. Hall Limited preview  2011 