An Improved Fuzzy Rule based Classifier for the Student's Performance Prediction |
Author(s): |
| Reena Yadav , LNCTE (Bhopal); Mrs. Rajni Kori, LNCTE (Bhopal); Dr. Rachna Dubey, LNCTE (Bhopal) |
Keywords: |
| Dataset, Classification, Clustering, Prediction, Data Mining, Sensitivity, Specificity |
Abstract |
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The Performance improvement of academic student's in higher education learning provides Turing point in the educational path in a decision manner using General Point Average. The algorithm implemented for the prediction of student's using Classification techniques provides an efficient way of predicting the performance of Student's Academic but the classification algorithms provides less Accuracy, ROC Curve and high error rate. Here in this paper an improved algorithm is implemented for the better classification of Student's academic performance. The proposed methodology implemented works in two Stages 1) by applying Fuzzy C-means Clustering algorithm to cluster the similar grouping of Student's data 2) by applying Fuzzy Decision tree based Classifier for the classification of Student's performance. The Methodology provides high Accuracy, ROC Curve and low error rate. |
Other Details |
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Paper ID: IJSRDV6I11001 Published in: Volume : 6, Issue : 1 Publication Date: 01/04/2018 Page(s): 1597-1600 |
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