Towards Identifying Multicriteria Outliers: An Outranking Relation-Based Approach

Baroudi Rouba and Safia Nait-Bahloul
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Baroudi Rouba: University of Abdelhamid Ibn Badis, Mostaganem, Algeria & LITIO Laboratory, University of Oran 1 Ahmed Benbella, Oran, Algeria
Safia Nait-Bahloul: LITIO Laboratory, University of Oran 1 Ahmed Benbella, Oran, Algeria

International Journal of Decision Support System Technology (IJDSST), 2018, vol. 10, issue 3, 27-38

Abstract: This article tackles the problem of outlier detection in the multicriteria decision aid (MCDA) field. The authors propose an outlier detection method based on binary outranking relations and Local Outlier Factor (LOF) algorithm. The outlier is detected by applying LOF algorithm on the distribution of the outranking relations generated by a multicriteria outranking method. The proposed approach is illustrated on an artificial example and evaluated on a real life financial problem, the country risk problem.

Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:igg:jdsst0:v:10:y:2018:i:3:p:27-38

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