Diversity Analysis for Ensembles of Word Sequence Recognisers
Identifieur interne : 001103 ( Main/Merge ); précédent : 001102; suivant : 001104Diversity Analysis for Ensembles of Word Sequence Recognisers
Auteurs : Roman Bertolami [Suisse] ; Horst Bunke [Suisse]Source :
- Lecture Notes in Computer Science [ 0302-9743 ] ; 2006.
Abstract
Abstract: In this paper we propose a general framework for analysing the diversity of ensembles of word sequence recognition systems. The goal of the framework is to enable the application of any diversity measure developed for standard multi-class classification problems to ensembles of word sequence recognisers. Experiments with several diversity measures are conducted on artificial as well as on real world data and show the effectiveness of the proposed approach.
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DOI: 10.1007/11815921_74
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<front><div type="abstract" xml:lang="en">Abstract: In this paper we propose a general framework for analysing the diversity of ensembles of word sequence recognition systems. The goal of the framework is to enable the application of any diversity measure developed for standard multi-class classification problems to ensembles of word sequence recognisers. Experiments with several diversity measures are conducted on artificial as well as on real world data and show the effectiveness of the proposed approach.</div>
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