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- ArticleFujita K.Nihon Kyosei Shika Gakkai Zasshi. 1978;37(4):381-4.
- BookWitten, I. H.; Frank, Eibe; Hall, Mark A.Contents:
Part I. Machine Learning Tools and Techniques:
1. What's it all about?
2. Input: concepts, instances, and attributes
3. Output: knowledge representation
4. Algorithms: the basic methods
5. Credibility: evaluating what's been learned
Part II. Advanced Data Mining:
6. Implementations: real machine learning schemes
7. Data transformation
8. Ensemble learning
9. Moving on: applications and beyond
Part III. The Weka Data Mining Workbench:
10. Introduction to Weka
11. The explorer
12. The knowledge flow interface
13. The experimenter
14 The command-line interface
15. Embedded machine learning
16. Writing new learning schemes
17. Tutorial exercises for the Weka explorer.Digital Access ScienceDirect 2011