Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Google eBook)

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Morgan Kaufmann, Jul 13, 2005 - Computers - 560 pages
42 Reviews
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
* 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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Review: Data Mining: Practical Machine Learning Tools and Techniques

User Review  - JDK1962 - Goodreads

I really, really wanted to like this book more than I did. After all, it was about a topic that I have great interest in, and describes a workbench application (Weka) that I can command-line access ... Read full review

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

User Review  - Kid - Goodreads

Best introductory book on Data Mining in terms of concepts and practice. Not too academically but goal-driven and data-driven, which makes readers understand it easier. WEKA is a great tool, although ... Read full review

All 7 reviews »

Contents

Machine learning tools and techniques
1
Concepts instances and attributes
41
Knowledge representation
61
Part II
80
4
83
2
89
5
91
5
143
The Explorer
369
Doing it again
377
Training and testing learning schemes
384
Clustering and association rules
391
Unsupervised instance filters
400
The Knowledge Flow interface
427
Analyzing the results
440
2
449

1
148
2
163
Applying the MDL principle to clustering
183
Engineering the input and output
285
3
345
198
347
The Weka machine learning workbench
363
Going through the code
462
computeInfoGain
480
201
497
Index
505
About the authors
525
Copyright

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About the author (2005)

University of Waikato, New Zealand

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