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Data mining practical machine learning tools and techniques

Data Mining: Practical Machine Learning Tools and Techniques 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. This highly anticipated third edition of the most acclaimed work o...

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Bibliographic Details
Main Authors: Witten, I. H., Frank, Eibe (Author), Hall, Mark A. (Author)
Format: eBook
Language:English
Published: Burlington, MA Morgan Kaufmann 2011, ©2011
Edition:3rd ed
Series:[Morgan Kaufmann series in data management systems]
Subjects:
Data Mining
Computers / Database Management / Data Mining / Bisacsh
Data Mining / Fast / (ocolc)fst00887946
Online Access:
Collection: Elsevier ScienceDirect eBooks - Collection details see MPG.ReNa
Table of Contents:
  • concepts, instances, and attributes
  • Output : knowledge representation
  • Algorithms : the basic methods
  • Credibility : evaluating what's been learned
  • Implementations : real machine learning schemes
  • Data transformation
  • Ensemble learning
  • Moving on : applications and beyond
  • Introduction to Weka
  • The explorer
  • The knowledge flow interface
  • The experimenter
  • The command-line interface
  • Embedded machine learning
  • Writing new learning schemes
  • Tutorial exercises for the weka explorer
  • Includes bibliographical references and index

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