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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.
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Submitted on : Monday, June 11, 2018 - 2:47:10 PM
Last modification on : Wednesday, November 3, 2021 - 6:17:44 AM
Long-term archiving on: : Wednesday, September 12, 2018 - 10:05:21 PM


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  • HAL Id : hal-01796289, version 1


Agus Budi Raharjo, Mohamed Quafafou, Faicel Chamroukhi. On Reliability of Majority Voting. Le 24th conférence de la Société Francophone de Classification (SFC 2017), Jun 2017, Lyon, France. ⟨hal-01796289⟩



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