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| LEADER |
00000cam a2200000 7i4500 |
| 001 |
0000083598 |
| 005 |
20131204093000.0 |
| 008 |
130530s2012 flu eng |
| 020 |
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|a 9781439830031 (hardback)
|
| 050 |
0 |
0 |
|a QA278.4
|b .Z47 2012
|
| 090 |
0 |
0 |
|a QA278.4
|b .Z47 2012
|
| 100 |
1 |
|
|a Zhou, Zhi-Hua ,
|e author
|
| 245 |
1 |
0 |
|a Ensemble methods :
|b foundations and algorithms
|c Zhi-Hua Zhou
|
| 260 |
|
|
|a Boca Raton, FL :
|b Taylor & Francis ,
|c 2012
|
| 300 |
|
|
|a xiv, 222 p. :
|b ill. ;
|c 25 cm.
|
| 490 |
0 |
|
|a Chapman & Hall/CRC machine learning & pattern recognition series
|
| 504 |
|
|
|a Includes bibliographical references (p. 187-218) and index
|
| 505 |
0 |
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|a 1. Introduction -- 2. Boosting -- 3. Bagging -- 4. Combination methods -- 5. Diversity -- 6. Ensemble pruning -- 7. Clustering Ensemble -- 8. Advanced Topics
|
| 520 |
|
|
|a "This comprehensive book presents an in-depth and systematic introduction to ensemble methods for researchers in machine learning, data mining, and related areas. It helps readers solve modem problems in machine learning using these methods. The author covers the spectrum of research in ensemble methods, including such famous methods as boosting, bagging, and rainforest, along with current directions and methods not sufficiently addressed in other books. Chapters explore cutting-edge topics, such as semi-supervised ensembles, cluster ensembles, and comprehensibility, as well as successful applications"-- Provided by publisher
|
| 650 |
|
0 |
|a Mathematical analysis
|
| 650 |
|
0 |
|a Multiple comparisons (Statistics)
|
| 650 |
|
0 |
|a Set theory
|
| 999 |
|
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|a 1000158341
|b Book
|c OPEN SHELF (30 DAYS)
|e Gong Badak Campus
|