| Description |
xxxi, 525 pages : illustrations ; 24 cm |
| Series |
Morgan Kaufmann series in data management systems |
|
Morgan Kaufmann series in data management systems.
|
| Contents |
Pt. I. Machine learning tools and techniques -- 1. What's it all about? -- 2. Input : concepts, instances, and 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 -- Pt. 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 |
| Summary |
"The book is a major revision of the first edition that appeared in 1999. While the basic core remains the same, it has been updated to reflect the changes that have taken place over five years, and now has nearly double the references. The highlights for the new edition include thirty new technique sections; an enhanced Weka machine learning workbench, which now features an interactive interface; comprehensive information on neural networks; a new section on Bayesian networks; plus much more."--BOOK JACKET |
| Bibliography |
Includes bibliographical references (pages 485-503) and index |
| Subject |
Data mining.
|
| Author |
Frank, Eibe.
|
| LC no. |
2005043385 |
| ISBN |
0120884070 |
|
