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Towards Identifying Multicriteria Outliers: An Outranking Relation-Based Approach

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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)

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.

Suggested Citation

  • Baroudi Rouba & Safia Nait-Bahloul, 2018. "Towards Identifying Multicriteria Outliers: An Outranking Relation-Based Approach," International Journal of Decision Support System Technology (IJDSST), IGI Global, vol. 10(3), pages 27-38, July.
    • Handle: RePEc:igg:jdsst0:v:10:y:2018:i:3:p:27-38
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