Modeling Academic Performance Evaluation using Fuzzy C-Means Clustering Techniques

In this paper we explore the applicability of Fuzzy C-Means clustering technique 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. This paper also presents a Fuzzy set and Regression analysis based rules based Fuzzy Expert System 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 C-Means clustering technique for academic performance evaluation.