01336cam a22002054a 4500 9780123748560 TZS 166250/= MUL eng AACR 006.312 WIT Witten, I. H. Data mining : practical machine learning tools and techniques / Ian H. Witten, Eibe Frank, Mark A. Hall. 3rd ed. Burlington, MA : Morgan Kaufmann, c2011. xxxiii, 629 p. : ill. ; 24 cm. Includes bibliographical references (p. 587-605) and index. 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. Data mining. Frank, Eibe. Hall, Mark A. BK 7046 7046 0 0 0 0 MU0001 MU0001 2015-03-03 FST(MU) 0 006.312 WIT 0079433 2022-12-12 00:00:00 1 2022-12-12 BK