Witten, I. H. <br/><br/>
Data mining : 

 - 3rd ed. 
 - Burlington, MA :  Morgan Kaufmann,  2011. 
 - xxxiii, 629 p. :  ill. ; 
 - [Morgan Kaufmann series in data management systems] .
<br/><br/>Part I. Machine Learning Tools and Techniques: 1. What's iIt 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 MiningWorkbench: 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. 
<br/><br/><label>ISBN: </label>9780123748560 (pbk.) 0123748569 (pbk.) 
<br/><br/><label>Subjects--Topical Terms: </label><br/>Data mining.
<br/><br/><label>LC Class. No.: </label>MED QA76.9.D343  / W58