Data Mining With Decision Trees: Theory And Applications (2nd Edition)
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A01=Lior Rokach
A01=Oded Z Maimon
Advanced Decision Trees
Author_Lior Rokach
Author_Oded Z Maimon
Category=UNF
Decision Forests
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eq_computing
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Evaluation of Classification Trees
Feature Selection
Fuzzy Decision Trees
Growing Decision Trees
Hybridization of Decision Trees with Other Techniques
Incremental Learning of Decision Trees
Introduction to Decision Trees
Pruning Trees
Sequence Classification Using Decision Trees
Splitting Criteria
Product details
- ISBN 9789814590075
- Publication Date: 23 Oct 2014
- Publisher: World Scientific Publishing Co Pte Ltd
- Publication City/Country: SG
- Product Form: Hardback
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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 edition, all chapters have been revised and new topics brought in. New topics include Cost-Sensitive Active Learning, Learning with Uncertain and Imbalanced Data, Using Decision Trees beyond Classification Tasks, Privacy Preserving Decision Tree Learning, Lessons Learned from Comparative Studies, and Learning Decision Trees for Big Data. A walk-through guide to existing open-source data mining software is also included in this edition.This book invites readers to explore the many benefits in data mining that decision trees offer:
