Bax, Eric (1997) Similar Classifiers and VC Error Bounds. California Institute of Technology , Pasadena, CA. (Unpublished) https://resolver.caltech.edu/CaltechCSTR:1997.cs-tr-97-14
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Abstract
We improve error bounds based on VC analysis for classes with sets of similar classifiers. We apply the new error bounds to separating planes and artificial neural networks.
| Item Type: | Report or Paper (Technical Report) |
|---|---|
| Additional Information: | © 1997 California Institute of Technology. |
| Group: | Computer Science Technical Reports |
| Subject Keywords: | machine learning, learning theory, generalization, Vapnik-Chervonenkis, separating planes, neural networks. |
| DOI: | 10.7907/Z9CZ355Q |
| Record Number: | CaltechCSTR:1997.cs-tr-97-14 |
| Persistent URL: | https://resolver.caltech.edu/CaltechCSTR:1997.cs-tr-97-14 |
| Usage Policy: | You are granted permission for individual, educational, research and non-commercial reproduction, distribution, display and performance of this work in any format. |
| ID Code: | 26815 |
| Collection: | CaltechCSTR |
| Deposited By: | Imported from CaltechCSTR |
| Deposited On: | 25 Apr 2001 |
| Last Modified: | 03 Oct 2019 03:18 |
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