ID3 Derived Fuzzy Rules for Predicting the Students Acedemic Performance

Anita Chaware, Dr. U.A Lanjewar
2014 IOSR Journal of Computer Engineering  
This paper presents a technique to use ID3 decision rules to produce fuzzy rules to get the optimize prediction of the students academic performance. In this paper, a the student administrative data for a class is used in order to classify the students final year marks in fuzzy logic prediction . This paper is using the machine learning approach to generate the rules so as to overcome the difficulties in a conventional approach like deriving fuzzy rules base from expert experience. This
more » ... ience. This research provides us with: a way to produce meaningful 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 the WEKA software and is utilized by the Fuzzy Inference System . A Fuzzy inference system was constructed to give the final crisp output. The ID3 was generated on 300 training data to get the better output. The output of our Fuzzy Student Performance Predictor was then tested on 50 test data to check for the accuracy.
doi:10.9790/0661-16685360 fatcat:7524oachp5dt7k272se5q7e5sm