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View all- Hu MWang Z(2024)A three-way confirmatory approach to formal concept analysis in classificationApplied Soft Computing10.1016/j.asoc.2024.111448155:COnline publication date: 1-Apr-2024
An Application of Bayesian Confirmation Theory for Three-Way Decision
Authors: 
Mengjun Hu, Xiaofei Deng, Yiyu YaoAuthors Info & Claims
Mengjun Hu, Xiaofei Deng, Yiyu YaoAuthors Info & ClaimsPages 3 - 15
Abstract
Bayesian confirmation theory studies how a piece of evidence confirms a hypothesis. In a qualitative approach, a piece of evidence may confirm, disconfirm, or be neutral with respect to a hypothesis. A quantitative approach uses Bayesian confirmation measures to evaluate the degree to which a piece of evidence confirms a hypothesis. In both approaches, we may perform a three-way classification of a set of pieces of evidence for a given hypothesis. The set of evidence is divided into three regions of positive evidence that confirms the hypothesis, negative evidence that disconfirms the hypothesis, and neutral evidence that neither confirms nor disconfirms the hypothesis. In this paper, we investigate three-way classification models in both qualitative and quantitative Bayesian confirmation approaches and explore their relationships to three-way classification models in rough set theory.
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Published In
Jun 2019
565 pages
ISBN:978-3-030-22814-9
DOI:10.1007/978-3-030-22815-6
© Springer Nature Switzerland AG 2019.
Publisher
Springer-Verlag
Berlin, Heidelberg
Publication History
Published: 17 June 2019
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View all- Hu MWang Z(2024)A three-way confirmatory approach to formal concept analysis in classificationApplied Soft Computing10.1016/j.asoc.2024.111448155:COnline publication date: 1-Apr-2024
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