Scale-sensitive Psi-dimensions: the Capacity Measures for Classifiers Taking Values in R^Q
| dc.creator | Guermeur, Yann | |
| dc.date | 2007-06-25 | |
| dc.date.accessioned | 2026-07-07T08:12:15Z | |
| dc.date.available | 2026-07-07T08:12:15Z | |
| dc.description | Bounds on the risk play a crucial role in statistical learning theory. They usually involve as capacity measure of the model studied the VC dimension or one of its extensions. In classification, such "VC dimensions" exist for models taking values in {0, 1}, {1,..., Q} and R. We introduce the generalizations appropriate for the missing case, the one of models with values in R^Q. This provides us with a new guaranteed risk for M-SVMs which appears superior to the existing one. | |
| dc.identifier | https://arxiv.org/abs/0706.3679 | |
| dc.identifier | http://arxiv.org/abs/0706.3679 | |
| dc.identifier | ASMDA 2007 (2007) 1-8 | |
| dc.identifier.uri | http://salesiana.dossiersoluciones.com/handle/123456789/132391 | |
| dc.subject | Machine Learning | |
| dc.title | Scale-sensitive Psi-dimensions: the Capacity Measures for Classifiers Taking Values in R^Q | |
| dc.type | text |