Data mining : practical machine learning tools and techniques
Material type:
- 9780123748560
Item type | Home library | Call number | Status | Date due | Barcode | |
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Biblioteca de la Facultad de Informática | H.2.8 WIT (Browse shelf(Opens below)) | Available | DIF-03870 |
Incluye índice y bibliografía
Part I. Machine Learning Tools and Techniques: -- 1. Whats iIt all about? -- 2. Input: concepts, instances, and attributes -- 3. Output: knowledge representation -- 4. Algorithms: the basic methods -- 5. Credibility: evaluating whats 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.