Data mining practical machine learning tools and techniques
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| Formato: | Libro |
| Idioma: | Inglés |
| Publicado: |
Amsterdam [etc.] :
Morgan Kaufman
2005.
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| Edición: | 2nd ed |
| Colección: | Morgan Kaufmann series in data management systems.
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| Materias: | |
| Ver en Universidad de Navarra: | https://unika.unav.edu/discovery/fulldisplay?docid=alma991001377159708016&context=L&vid=34UNAV_INST:VU1&search_scope=34UNAV_TODO&tab=34UNAV_TODO&lang=es |
Tabla de Contenidos:
- Part I: Machine learning tools and techniques. 1. What’s it all about? 2. Input: Concepts, instances, attributes 3. Output: Knowledge representation 4. Algorithms: The basic methods 5. Credibility: Evaluating what’s been learned 6. Implementations: Real machine learning schemes 7. Transformations: Engineering the input and output 8. Moving on: Extensions and applications Part II: The Weka machine learning workbench . 9. Introduction to Weka 10. The Explorer 11. The Knowledge Flow interface 12. The Experimenter 13. The command-line interface 14. Embedded machine learning 15. Writing new learning schemes
