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Performance Analysis of Classification Algorithms for Prediction of Student Failure in College using Academic Data Processing

Author(s):

Trupti Diwan , MIT College of Engineering , Pune; Bharati Dixit, MIT College of Engineering , Pune

Keywords:

Educational Data Mining, Classification Algorithms, Student Failure, Decision Tree, WEKA, Prediction

Abstract

Student data sets give useful information about efficient educational knowledge. Student failure affects education quality. A data mining approach is applied to predict student failure in college at MIT College of engineering Pune, based on internal marks and external marks. Three different classification algorithms, AD Tree, LAD Tree, and ICRM, are employed to build prediction model. This paper summarizes and compares three different classification algorithms. In the end, accuracy of three algorithms is analyzed. The results show that ICRM algorithm has obtained highest TN Rate and GM compared to other algorithms. So the accuracy of prediction is more accurate.

Other Details

Paper ID: IJSRDV3I70060
Published in: Volume : 3, Issue : 7
Publication Date: 01/10/2015
Page(s): 120-124

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