A comparison of Neural Network and SVM on the multi-label classification of Quran verses topic in English translation

Abstract

Indeed the Quran is the main guideline for Muslims. The enticing thing in the Quran is one verse of the Quran can be classified into more than one topic of discussion in the Quran, for example one verse discusses about prayer and faith or arkanul Islam and religions, thus this called multilabel case. In this study, we compared the multi-label Quran verse topic classification techniques using Na¨ıve bayes, ANN and SVM. Based on the experiment conducted, combination Na¨ıve Bayes algorithm with Mutual Information or Information Gain gives the best performance when it applied to construct the model with Hamming Loss of 0.0938.