ID3 Derived Fuzzy Rules for Predicting the Students AcedemicPerformance
Journal Title: IOSR Journals (IOSR Journal of Computer Engineering) - Year 2014, Vol 16, Issue 6
Abstract
Abstract: This paper presents a technique to use ID3 decision rules to produce fuzzy rules to get the optimizeprediction of the students academic performance. In this paper, a the student administrative data for a class isused in order to classify the students final year marks in fuzzy logic prediction . This paper is using the machinelearning approach to generate the rules so as to overcome the difficulties in a conventional approach likederiving fuzzy rules base from expert experience. This research provides us with: a way to producemeaningful and simple fuzzy rules; a method to fuzzify ID3-derived rules to deal with many inputs variables;and a de-fuzzification system to get the output in human understandable form. The Id3 tree is generated by theWEKA software and is utilized by the Fuzzy Inference System . A Fuzzy inference system was constructed to givethe final crisp output. The ID3 was generated on 300 training data to get the better output. The output of ourFuzzy Student Performance Predictor was then tested on 50 test data to check for the accuracy.
Authors and Affiliations
Anita Chaware , Dr. U. A. Lanjewar
Keywords
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