1. Dynamic ensemble selection based on classifier competence of margin.
- Author
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Chen Rui, Huang Haijun, Huang Wen, and Hu Jingsong
- Abstract
This paper proposed a new ordering criterion which could be used by classifiers selection algorithm based on ordered aggregation. For calculating the competence of the classifier, it used a randomized reference classifier for modeling the classifier to get the probabilistic model of classifier competence. By combining with ordering criterion based on classifier competence of margin, the paper proposed a novel dynamic ensemble selection algorithm(CCM-DES) for improving the performance of the ensemble. CCM-DES first divided feature space into different regions, and then constructed optimal ensembles in every region. It used DES for classify the unlabeled sample at last. Experiments on UCI datasets show that the criterion based on margin classifiers competence is better than current ordering criterion. Furthermore, CCM-DES has the advantages of smaller ensembles, higher accuracy, shorter classifying time than current ensemble algorithm. [ABSTRACT FROM AUTHOR]
- Published
- 2015
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