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Machine learning : the art and science of algorithms that make sense of data / Peter Flach.
Materialtyp:
TextSpråk: Engelska Utgivningsuppgift: Cambridge : Cambridge University Press, 2012Beskrivning: xvii, 396 pages illustrations 25 cmInnehållstyp: - text
- unmediated
- volume
- 9781107096394
- 1107096391
- 9781107422223
- 1107422221
- 006.31 23
- Q325.5 .F53 2012
- Pud
Innehåll:
Abstrakt: 'Machine Learning' brings together all the state-of-the-art methods for making sense of data. With hundreds of worked examples and explanatory figures, it explains the principles behind these methods in an intuitive yet precise manner and will appeal to novice and experienced readers alike.
1. The ingredients of machine learning -- 2. Binary classification and related tasks -- 3. Beyond binary classification -- 4. Concept learning -- 5. Tree models -- 6. Rule models -- 7. Linear models -- 8. Distance-based models -- 9. Probabilistic models -- 10. Features -- 11. Model ensembles -- 12. Machine learning experiments -- Epilogue: where to go from here.
| Exemplartyp | Aktuellt bibliotek | Hyllsignatur | Status | Förfallodatum | Streckkod | Exemplarreservationer | |
|---|---|---|---|---|---|---|---|
| Bok (Hemlån) | Campus Karlskrona | 006.3 | Tillgänglig | 080041486800 | |||
| Bok (Hemlån) | Campus Karlskrona | 006.3 | Tillgänglig | 080047626402 | |||
| Bok (Hemlån) | Campus Karlskrona | 006.3 | Utlånad | 2025-01-28 | 080047624376 | ||
| Bok (Dagslån) | Campus Karlskrona Referens | 006.3 | Tillgänglig | 080047624375 | |||
| Bok (Hemlån) | Campus Karlskrona | 006.3 | Utlånad | 2025-01-28 | 080041486801 |
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Includes bibliographical references (pages 367-381) and index.
1. The ingredients of machine learning -- 2. Binary classification and related tasks -- 3. Beyond binary classification -- 4. Concept learning -- 5. Tree models -- 6. Rule models -- 7. Linear models -- 8. Distance-based models -- 9. Probabilistic models -- 10. Features -- 11. Model ensembles -- 12. Machine learning experiments -- Epilogue: where to go from here.
'Machine Learning' brings together all the state-of-the-art methods for making sense of data. With hundreds of worked examples and explanatory figures, it explains the principles behind these methods in an intuitive yet precise manner and will appeal to novice and experienced readers alike.