01901nam a2200409 4500 DLU110129141 ##20111216 ##101005s2011 maua b 001 0 eng 2010039827 0123748569 (pbk.) 9780123748560 (pbk.) (OCoLC)ocn262433473 DLC DLC YDX BTCTA YDXCP BWX DEBSZ CDX IUL DLC pcc 006.3 WI-I Witten, I. H. (Ian 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. Morgan Kaufmann series in data management systems. 19/2011 GT 1667757 DLU True Đào Thị Thu Huyền G A SH Thư viện Trường Đại học Đà Lạt