Finding peculiar students from student database using outlier analysis: Data mining approach

Abstract

Students with different behaviors joined in the educational institutions create different problems in class. To bring them in right path, mentors should be able to find such candidates in the class. Since these students are different in behavior, the teaching faculty should not teach the common approach of teaching for all students. These people would have abnormal behavior when compared with other students. These students are treated as peculiar students. The Students data is almost mixed type of data. In this paper how these peculiar students are found using data mining techniques is presented. In this paper the techniques related to categorical attribute data are used. The data is collected from B.Tech students from different colleges for experiments using ILS questionnaire [1]. We have also investigated the relationship of peculiarity with learning styles.