In today’s competitive world of educational organizations, the universities and colleges are using various data mining tools and techniques to improve the students’ performance. Now a days, when the number of drop out students is increasing every year, if we get to know the probability of a student whether he/she will be able to cope up easily with the course, it is possible to take some preventive actions beforehand. In other words, if we get to know that a student will clear his papers in the course or he will have reappear in papers, a teacher/parent can focus more on such students. The data set of students has been taken from the UCI Machine Learning repository where a sample of 131 students have been provided with twenty-two attributes. The results of six classification algorithms have been compared in order to predict the most appropriate model for classifying whether a student will have a reappear in a course or not.
CITATION STYLE
Aggarwal, D., Mittal, S., & Bali, V. (2019). Prediction model for classifying students based on performance using machine learning techniques. International Journal of Recent Technology and Engineering, 8(2 Special Issue 7), 496–503. https://doi.org/10.35940/ijrte.B1093.0782S719
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