| LIBRARY OF CONGRESS CONTROL NUMBER |
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| LC control number |
2010039827 |
| INTERNATIONAL STANDARD BOOK NUMBER |
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| International Standard Book Number |
9780123748560 (pbk.) |
| INTERNATIONAL STANDARD BOOK NUMBER |
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| International Standard Book Number |
0123748569 (pbk.) |
| DEWEY DECIMAL CLASSIFICATION NUMBER |
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| Call number |
006.3/12 |
| MAIN ENTRY--PERSONAL NAME |
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| Authors |
Witten, I. H. |
| TITLE STATEMENT |
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| Title |
Data mining : |
| Subtitle |
practical machine learning tools and techniques. |
| EDITION STATEMENT |
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| Edition |
3rd ed. |
| PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) |
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| Place of publication |
Burlington, MA : |
| Publisher |
Morgan Kaufmann, |
| Date |
c2011. |
| PHYSICAL DESCRIPTION |
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| Extent |
xxxiii, 629 p. : |
| Other Details |
ill. ; |
| Size |
24 cm. |
| SERIES STATEMENT |
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| Series statement |
[Morgan Kaufmann series in data management systems] |
| GENERAL NOTE |
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| General note |
The third edition of this practical guide to machine learning and data mining is fully updated to account for technological advances since its previous printing in 2005 and is now even more closely aligned with the use of the Weka open source machine learning, data mining and data modeling application. Beginning with an introduction to data mining, the volume explores basic inputs, outputs and algorithms, the implementation of machine learning schemes and in-depth exploration of the many uses of the Weka data analysis software. Numerous illustration, tables and equations are included throughout and additional resources are available through a companion website. Witten, Frank and Hall are academics with the department of computer science at the University of Waikato, New Zealand, the home of the Weka software project. |
| CONTENTS |
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| Contents |
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. |
| SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical Heading |
Data mining. |
| ADDED ENTRY |
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| Name |
Frank, Eibe. |
| ADDED ENTRY |
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| Name |
Hall, Mark A. |
| SERIES UNIFORM TITLE |
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| Series Uniform Title |
Morgan Kaufmann series in data management systems. |
| ELECTRONIC LOCATION AND ACCESS |
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| Uniform Resource Identifier |
https://uowd.box.com/s/vputfhdosh2virihawmxbswm3z4qgk21 |
| Public note |
Location Map |
| MAIN ENTRY--PERSONAL NAME |
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39045 |
| SUBJECT ADDED ENTRY--TOPICAL TERM |
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312 |
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313 |
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314 |
| SERIES UNIFORM TITLE |
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39126 |