A Comparative Analysis of classification data mining techniques : Deriving key factors useful for predicting students performance
A Comparative Analysis of classification data mining techniques : Deriving key factors useful for predicting students performance
Muhammed Salman Shamsi,J. Lakshmi
2016
2 Citations
TLDR
This paper performs a comparative analysis of various classification techniques, such as Naive Bayes, LibSVM, J48, Random Forest, and JRip and tries to choose best among these and finds that Naives Bayes is the most accurate method in terms of students failure prediction andJRip is most accurate in termsof students grade prediction.