Data Mining: Practical Machine Learning Tools and Techniques With Java Implementations

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Morgan Kaufmann Publ., 2000 - Computers - 371 pages
19 Reviews

This book offers a thorough grounding in machine learning concepts as well as practical advice on applying machine learning tools and techniques in real-world 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 mining including both tried-and-true techniques of the past and Java-based 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 platform-independent 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  - Juliusz Gonera - Goodreads

Very hands on/practical intro to the subject. For readers who want to start using ML techniques quickly and worry about theoretical considerations later. Read full review

Review: Data Mining: Practical Machine Learning Tools and Techniques with Java Implementations (The Morgan Kaufmann Series in Data Management Systems)

User Review  - David - Goodreads

A gentle introduction Read full review

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Contents

Whats it all about?
1
Concepts instances attributes
37
Knowledge representation
57
Copyright

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citeulike: Data Mining: Practical Machine Learning Tools and ...
TY - BOOK ID - citeulike:167557 TI - Data Mining: Practical Machine Learning Tools and Techniques with Java Implementations PB - {Morgan Kaufmann} SN ...
www.citeulike.org/ user/ sb-3000/ article/ 167557

Data Mining: Practical Machine Learning Tools and Techniques with ...
Data Mining: Practical Machine Learning Tools and. Techniques with Java Implementations. by/an H. Witten and Eibe Frank. Morgan Kaufmann Publishers, 2000 ...
portal.acm.org/ ft_gateway.cfm?id=507355& type=pdf& dl=GUIDE& dl=ACM

PII: S0004-3702(01)00124-2
Artificial Intelligence 131 (2001) 191–198. Book Review. Two machine learning textbooks:. An instructor’s perspective. ✩. Ernest Davis ...
linkinghub.elsevier.com/ retrieve/ pii/ S0004370201001242

Weka: Practical Machine Learning Tools and Techniques with Java ...
Weka: Practical Machine Learning Tools and Techniques. with Java Implementations. Ian H. Witten, Eibe Frank, Len Trigg, Mark Hall, Geoffrey Holmes, ...
www.cs.waikato.ac.nz/ ~ml/ publications/ 1999/ 99IHW-EF-LT-MH-GH-SJC-Tools-Java.pdf

Decision Trees and Data-mining Books | Decision Trees & Data Mining
Data Mining: Practical Machine Learning Tools and Techniques with Java Implementations. Authors: ih Witten and E. Frank; Publisher: Morgan Kaufmann; ...
www.decisiontrees.net/ node/ 19

Knowledge Discovery in Data Bases
4.1, 9.1, 9.4, 10.1); ih Witten, E. Frank: Data Mining: Practical Machine Learning Tools and Techniques with Java Implementations. The Morgan Kaufmann, 1999 ...
www.ailab.si/ blaz/ predavanja/ ozp/

Download this chapter on data mining
Takeaway: Download this excerpt from Data Mining: Practical Machine Learning Tools and Techniques with Java Implementations, published by Morgan-Kauffmann, ...
articles.techrepublic.com.com/ 5100-10878-1034541.html

580Syllabus
Required text: Ian H. Witten and Eibe Frank, Data Mining: Practical Machine Learning Tools and Techniques with Java Implementations, Morgan Kaufmann, 1999, ...
www.cs.ccsu.edu/ ~markov/ ccsu_courses/ DataMining.html

Principles of Data Mining
Witten, ih, and Frank, E. (2000), Data Mining: Practical Machine Learning Tools and Techniques With Java Implementations, San Fransisco, CA: Morgan Kaufmann ...
www.questia.com/ PM.qst?a=o& se=gglsc& d=5002529562

CS 539 Spring 2005 - Syllabus
"Data Mining: Practical Machine Learning Tools and Techniques with Java Implementations". Morgan Kaufmann Publishers. 2000. S. Russell, P. Norvig. ...
www.cs.wpi.edu/ ~cs539/ s05/

About the author (2000)

University of Waikato, New Zealand

Eibe Frank lives in New Zealand with his Samoan spouse and two lovely boys, but originally hails from Germany, where he received his first degree in computer science from the University of Karlsruhe. He moved to New Zealand to pursue his Ph.D. in machine learning under the supervision of Ian H. Witten, and joined the Department of Computer Science at the University of Waikato as a lecturer on completion of his studies. He is now an associate professor at the same institution. As an early adopter of the Java programming language, he laid the groundwork for the Weka software described in this book. He has contributed a number of publications on machine learning and data mining to the literature and has refereed for many conferences and journals in these areas.

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