A PROMETHEE-based classification method using concordance and discordance relations and its application to bankruptcy prediction

Authors:
Yi-Chung Hu;Chiung-Jung Chen
Affiliations:
Department of Business Administration, Chung Yuan Christian University, Chung-Li 32023, Taiwan, ROC;Department of Business Administration, Chung Yuan Christian University, Chung-Li 32023, Taiwan, ROC
Venue:
Information Sciences: an International Journal
Year:
2011

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Abstract

Outranking relation theory has been widely used to study pattern classification. Here we propose a classification method with concepts from the flows used in PROMETHEE methods, which are extensively applied in multi-criteria decision aids. PROMETHEE uses a flow, generated on the basis of a preference index and measured by various preference functions for each criterion, to represent the preference intensity for one pattern over another pattern. However, only criteria that are concordant with the preference contribute to a preference index. In the present study, the opinions from discordant criteria are also taken into account. The proposed method newly defines an overall preference index using both concordance and discordance relations for ordinal sorting problems. The final classification decision for a new pattern depends on its net flow. The criteria weights are determined using a genetic-algorithm-based approach. Empirical results obtained for a real-world problem regarding bankruptcy prediction demonstrate that the proposed method performs well compared to other well-known classification methods.