01728nam a2200301 a 4500 vtls000056575 KUKTEM 20251125093043.0 111205t2011 maua f 001 0 eng d 9780123748560 (pbk.) 0123748569 (pbk.) 201204021030 asmadi 201112051102 sri UMP QA76.9.D343 W58 2011 Witten, Ian H. Data mining : practical machine learning tools and techniques / Ian H. Witten, Eibe Frank, Mark A. Hall 3rd ed. Burlington, MA. : Morgan Kaufmann, 2011 xxxiii, 629 p. : ill. ; 24 cm. Morgan Kaufmann series in data management systems 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. 0 0 0 0 20000 20000 2019-09-04 204.68 1 QA76.9.D343 W58 2011 0000064037 2023-11-03 00:00:00 2023-10-16 1 204.68 2019-09-04 OPEN VIRTUA40 60930 60936 VTLSSORT0080*0200*0201*0400*0900*1000*2450*2500*2600*3000*4900*5040*5050*6500*7000*7001*9991 1