Cascading Regularized Classifiers
Among the various methods to combine classifiers, Boosting was originally thought as an stratagem to cascade pairs of classifiers through their disagreement. I recover the same idea from the work of Niyogi et al. to show how to loosen the requirement of weak learnability, central to Boosting, and in...
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| Language: | en_US |
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2005
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| Online Access: | http://hdl.handle.net/1721.1/30463 |
| _version_ | 1811098099452477440 |
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| author | Perez-Breva, Luis |
| author_facet | Perez-Breva, Luis |
| author_sort | Perez-Breva, Luis |
| collection | MIT |
| description | Among the various methods to combine classifiers, Boosting was originally thought as an stratagem to cascade pairs of classifiers through their disagreement. I recover the same idea from the work of Niyogi et al. to show how to loosen the requirement of weak learnability, central to Boosting, and introduce a new cascading stratagem. The paper concludes with an empirical study of an implementation of the cascade that, under assumptions that mirror the conditions imposed by Viola and Jones in [VJ01], has the property to preserve the generalization ability of boosting. |
| first_indexed | 2024-09-23T17:09:53Z |
| id | mit-1721.1/30463 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T17:09:53Z |
| publishDate | 2005 |
| record_format | dspace |
| spelling | mit-1721.1/304632019-04-12T08:37:45Z Cascading Regularized Classifiers Perez-Breva, Luis AI Among the various methods to combine classifiers, Boosting was originally thought as an stratagem to cascade pairs of classifiers through their disagreement. I recover the same idea from the work of Niyogi et al. to show how to loosen the requirement of weak learnability, central to Boosting, and introduce a new cascading stratagem. The paper concludes with an empirical study of an implementation of the cascade that, under assumptions that mirror the conditions imposed by Viola and Jones in [VJ01], has the property to preserve the generalization ability of boosting. 2005-12-22T01:27:18Z 2005-12-22T01:27:18Z 2004-04-21 MIT-CSAIL-TR-2004-023 AIM-2004-028 http://hdl.handle.net/1721.1/30463 en_US Massachusetts Institute of Technology Computer Science and Artificial Intelligence Laboratory 8 p. 8847621 bytes 505102 bytes application/postscript application/pdf application/postscript application/pdf |
| spellingShingle | AI Perez-Breva, Luis Cascading Regularized Classifiers |
| title | Cascading Regularized Classifiers |
| title_full | Cascading Regularized Classifiers |
| title_fullStr | Cascading Regularized Classifiers |
| title_full_unstemmed | Cascading Regularized Classifiers |
| title_short | Cascading Regularized Classifiers |
| title_sort | cascading regularized classifiers |
| topic | AI |
| url | http://hdl.handle.net/1721.1/30463 |
| work_keys_str_mv | AT perezbrevaluis cascadingregularizedclassifiers |