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Beschreibung
The book explores connections between Riemannian geometry and several well known machine learning techniques, including boosting and logistic regression. In addition to providing motivation for these techniques, the book provides a mechanism for designing new statistical procedures that are shown experimentally to outperform the state-of-the-art. This work follows up on traditional information geometry with a more applied machine learning perspective.
Details
| Verlag | LAP LAMBERT Academic Publishing |
| Ersterscheinung | 27. Januar 2015 |
| Maße | 22 cm x 15 cm x 0.9 cm |
| Gewicht | 227 Gramm |
| Format | Softcover |
| ISBN-13 | 9783659682025 |
| Seiten | 140 |
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