Witten, Ian H. <br/><br/>
Data mining :  practical machine learning tools and techniques 

 - 3rd ed. 
 - Amsterdam :   Morgan Kaufmann,  2011 
 - xxxiii, 629 p. :  il. ;  24 cm. 
<br/><br/> Incluye índice y bibliografía 
<br/><br/>Part I. Machine Learning Tools and Techniques:  --  1. Whats iIt all about? --  2. Input: concepts, instances, and attributes  --  3. Output: knowledge representation  --  4. Algorithms: the basic methods  --  5. Credibility: evaluating whats 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 
<br/><br/><label>Standard No.: </label>DIF005356 
<br/><br/><label>Subjects--Topical Terms: </label><br/>MINERÍA DE DATOS
<br/><br/><label>Subjects--Index Terms: </label>aprendizaje automático