Modeling Academic Performance Evaluation Using Subtractive Clustering Approach
نویسندگان
چکیده
In this paper, we explore the applicability of Subtractive Clustering Technique (SCT) to student allocation problem that allocates new students to homogenous groups of specified maximum capacity, and analyze effects of such allocations on the academic performance of students. The paper also presents a Fuzzy set, Subtractive Clustering Technique (SCT) and regression analysis based Subtractive Clustering Fuzzy Expert System (SCFES) model which is capable of dealing with imprecision and missing data that is commonly inherited in the student academic performance evaluation. This model automatically converts crisp sets into fuzzy sets by using SCT.
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