Abstract: Highlights•A criterion preference-based decision risk loss measure method is proposed.•An AP clustering algorithm is utilized to obtain the description of the objects.•Three conditional probability estimation approaches are established.•Three three-way MCDM models fusing multiple criterion preferences are developed.
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