Data mining : practical machine learning tools and techniques

Data mining : practical machine learning tools and techniques

Bibliographic Details
Main Authors: Witten, Ian H. (Author), Frank, Eibe (Author), Hall, Mark A. (Author), Pal, Christopher J. (Author)
Format: Book
Language:English
Edition:Fourth edition
Subjects:
Data mining
Table of Contents:
  • 1. What's it all about
  • 2. Input; concepts, instance, attributes
  • 3. Output: knowledge representation
  • 4. Algorithms: the basic methods
  • 5. Credibility:evaluating what's been learned
  • 6. Tress and rules
  • 7. extending instance-based and linear models
  • 8. data transformations
  • 9. Probabilistics methods
  • 10. deep learning
  • 11. Beyond supervised and unsupervised learning
  • 12. Ensemble learning
  • 13. Moving on: applications and beyond

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