On Reliability of Majority Voting
Abstract
In ensemble learning field, the voting of different experts can produce an optimal solution. However, the quality of voting depends on the participant expertise. In this paper, an expert selection algorithm is proposed by considering reliability measure extracted from the confidence score. Our method has been applied based on the combination of 6 algorithms. Experimental result using 8 datasets shows that the proposed reliable majority voting algorithm provides a better average accuracy than the ordinary majority voting and the base classi-fiers. keyword: reliable majority voting, classification, ensemble learning.
Domains
Machine Learning [cs.LG]
Origin : Files produced by the author(s)
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