Data mining : practical machine learning tools and techniques / Ian H. Witten, Eibe Frank, Mark A. Hall.
Material type:
TextSeries: Morgan Kaufmann series in data management systemsPublication details: Burlington, MA : Morgan Kaufmann, c2011.Edition: 3rd edDescription: xxxiii, 629 p. : ill. ; 24 cmContent type: - text
- unmediated
- volume
- 9780123748560 (pbk.)
- 0123748569 (pbk.)
- 006.312 22 W.I.D
- QA76.9.D343 W58 2011
| Item type | Current library | Collection | Call number | Status | Date due | Barcode | |
|---|---|---|---|---|---|---|---|
Books
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Main library A2 | Computers & Information Technology ( Information systems ) | 006.312 W.I.D (Browse shelf(Opens below)) | Available | 00009288 |
Browsing Main library shelves, Shelving location: A2 Close shelf browser (Hides shelf browser)
| 006.312 R.L.D Data mining with decision trees : theory and applications / | 006.312 T.P.I Introduction to Data Mining / | 006.312 W.H.D Data insights : new ways to visualize and make sense of data / | 006.312 W.I.D Data mining : practical machine learning tools and techniques / | 006.312 X.G.A Applied data mining / | 006.312 Z.M.D Data mining and analysis : fundamental concepts and algorithms / | 006.312 Z.Z.S Spectral feature selection for data mining / |
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.
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