Panel matrix and ranking model recovery using mixed-scale measured data

A decision-making problem is solved in the field of operational research education. The paper presents a method for recovery of changes in ratings of student employees. These ratings are based on interviews at the information technology (IT) training center. A dataset consisting of expert estimates for assessments for different years and overall rating for these students is considered. The scales of the expert estimates vary from year to year, but the scale of the rating remains stable. One should recover the time-independent ranking model. The problem is stated as the object–feature–year panel matrix recovery. It is a map from student descriptions (or their generalized portraits) to expected ratings for all years. Also, a stability of the ranking model produced by the panel matrix is studied. A new method of panel matrix recovery is suggested. It is based on a solution of multidimensional assignment problem. To construct a ranking model, an ordinal classification algorithm with partially ordered feature sets and an algorithm based on support vector machine have been used. The problem is illustrated by the dataset containing the expert assessment of the student interviews at the IT center.

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