Learning styles vs suitable courses

Most of the students are forced to take different courses based on their parent´s interest, not of their interest. Some students are selecting their courses without knowing their inner ability. In this paper, how the student should select the different courses based on their learning styles in different levels is derived. This is achieved by eliminating the outliers in collected data from students. Since the data collected from students based on their learning styles is categorical, outlier detection analysis for categorical data is used to eliminate outliers from this data. These outliers are occurred while collecting data from students. Because some students are very peculiar, some students are not interested to reveal their data, some students may give wrong answers for any questionnaire by bias and some students may give incomplete data due to lack of time. The data is collected from B.Tech students from different colleges for experiments. After eliminating outliers from this data by proposed outliers´ techniques, different classifiers are applied to frame set of rules to select suitable courses based on their learning styles. The results are better when proposed method is applied.