Time–Adaptive Support Vector Machines
In this work we propose an adaptive classification method able both to learn and to follow the temporal evolution of a drifting concept. With that purpose we introduce a modified SVM classifier, created using multiple hyperplanes valid only at small temporal intervals (windows). In contrast to oth...
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Autores principales: | , , |
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Formato: | Artículo |
Lenguaje: | en_US |
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Asociación Española de Inteligencia Artificial
2011
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Materias: | |
Acceso en línea: | http://hdl.handle.net/2133/1718 http://hdl.handle.net/2133/1718 |
Aporte de: |
id |
I15-R121-2133-1718 |
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record_format |
dspace |
institution |
Universidad Nacional de Rosario |
institution_str |
I-15 |
repository_str |
R-121 |
collection |
Repositorio Hipermedial de la Universidad Nacional de Rosario (UNR) |
language |
en_US |
orig_language_str_mv |
en_US |
topic |
Adaptive methods Support Vector Machine Drifting concepts |
spellingShingle |
Adaptive methods Support Vector Machine Drifting concepts Grinblat, Guillermo Granitto, Pablo M. Ceccatto, Alejandro Time–Adaptive Support Vector Machines |
topic_facet |
Adaptive methods Support Vector Machine Drifting concepts |
description |
In this work we propose an adaptive classification method able both to learn and to follow the temporal
evolution of a drifting concept. With that purpose we introduce a modified SVM classifier, created using
multiple hyperplanes valid only at small temporal intervals (windows). In contrast to other strategies
proposed in the literature, our method learns all hyperplanes in a global way, minimizing a cost function
that evaluates the error committed by this family of local classifiers plus a measure associated to the VC
dimension of the family. We also show how the idea of slowly changing classifiers can be applied to non-linear
stationary concepts with results similar to those obtained with normal SVMs using gaussian kernels. |
format |
Article |
author |
Grinblat, Guillermo Granitto, Pablo M. Ceccatto, Alejandro |
author_facet |
Grinblat, Guillermo Granitto, Pablo M. Ceccatto, Alejandro |
author_sort |
Grinblat, Guillermo |
title |
Time–Adaptive Support Vector Machines |
title_short |
Time–Adaptive Support Vector Machines |
title_full |
Time–Adaptive Support Vector Machines |
title_fullStr |
Time–Adaptive Support Vector Machines |
title_full_unstemmed |
Time–Adaptive Support Vector Machines |
title_sort |
time–adaptive support vector machines |
publisher |
Asociación Española de Inteligencia Artificial |
publishDate |
2011 |
url |
http://hdl.handle.net/2133/1718 http://hdl.handle.net/2133/1718 |
work_keys_str_mv |
AT grinblatguillermo timeadaptivesupportvectormachines AT granittopablom timeadaptivesupportvectormachines AT ceccattoalejandro timeadaptivesupportvectormachines |
bdutipo_str |
Repositorios |
_version_ |
1764820410587676675 |