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Data mining with decision trees : theory and applications

Author: Lior Rokach; Oded Maimon
Publisher: New Jersey : World Scientific, [2015] ©2015
Series: Series in machine perception and artificial intelligence, Volume 81.
Edition/Format:   eBook : Document : English : 2nd editionView all editions and formats
Summary:
Decision trees have become one of the most powerful and popular approaches in knowledge discovery and data mining; it is the science of exploring large and complex bodies of data in order to discover useful patterns. Decision tree learning continues to evolve over time. Existing methods are constantly being improved and new methods introduced. This 2nd Edition is dedicated entirely to the field of decision trees in  Read more...
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Genre/Form: Electronic books
Additional Physical Format: Print version:
Rokach, Lior.
Data mining with decision trees : theory and applications.
Singapore : World Scientific Publishing Company, ©2015
xxi, 305 pages
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Lior Rokach; Oded Maimon
ISBN: 9789814590082 9814590088
OCLC Number: 893673231
Description: 1 online resource (xxi, 305 pages) : illustrations.
Contents: Introduction to Decision Trees; Growing Decision Trees; Evaluation of Classification Trees; Splitting Criteria; Pruning Trees; Advanced Decision Trees; Decision Forests; Incremental Learning of Decision Trees; Feature Selection; Fuzzy Decision Trees; Hybridization of Decision Trees with Other Techniques; Beyond Classification Tasks; Privacy Preserving Decision Tree Learning; Decision Tees Learning in Uncertain and Imbalanced Data; Decision Trees Performance Analysis: Lessons Learned from Comparative Studies; Fast induction of Decision Trees and Big Data; Using Existing Software - A Walk-through Guide.
Series Title: Series in machine perception and artificial intelligence, Volume 81.
Responsibility: Lior Rokach, Oded Maimon.

Abstract:

Decision trees have become one of the most powerful and popular approaches in knowledge discovery and data mining; it is the science of exploring large and complex bodies of data in order to discover useful patterns. Decision tree learning continues to evolve over time. Existing methods are constantly being improved and new methods introduced. This 2nd Edition is dedicated entirely to the field of decision trees in data mining; to cover all aspects of this important technique, as well as improved or new methods and techniques developed after the publication of our first edition. In this new ed.

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