Knowledge discovery with support vector machines Lutz Hamel.
Material type:
TextSeries: Wiley series on methods and applications in data mining: Publisher: Hoboken, N.J. : John Wiley & Sons, �2009Description: xv, 246 pages : illustrations ; 25 cmISBN: 9780470371923; 0470371927; 9780470503041; 0470503041Subject(s): Support vector machines | Data mining | Machine learning | Computer algorithms | Computer algorithms | Data mining | Machine learning | Support vector machinesDDC classification: 001.64 LOC classification: Q325.5 | .H38 2009| Item type | Current location | Call number | Status | Date due | Barcode |
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Reference
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GKVK Library | 001.64 HAM (Browse shelf) | Not for loan | 134098 |
Includes bibliographical references and index.
1. What is knowledge discovery? -- 2. Knowledge discovery environments -- 3. Describing data mathematically -- 4. Linear decision surfaces and functions -- 5. Perception learning -- 6. Maximum-margin classifiers -- 7. Support vector machines -- 8. Implementation -- 9. Evaluating what has been learned -- 10. Elements of statistical learning theory -- 11. Multiclass classification -- 12. Regression with support vector machines -- 13. Novelty detection -- Appendix A : Notation -- Appendix B : Tutorial introduction to R.
"This book provides an in-depth, easy-to-follow introduction to support vector machines drawing only from minimal, carefully motivated technical and mathematical background material. Complemented with hands-on exercises, algorithm descriptions, and data sets, Knowledge Discovery with Support Vector Machines is an invaluable textbook for advanced undergraduate and graduate courses. It is also an excellent tutorial on support vector machines for professionals who are pursuing research in machine learning and related areas."--Jacket.
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