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All Journal International Journal of Informatics and Communication Technology (IJ-ICT)
Hadeel N. Alshaer
Amman Arab University
Computer Science & IT

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Improved ICHI square feature selection method for Arabic classifiers Hadeel N. Alshaer; Mohammed A. Otair; Laith Abualigah
International Journal of Informatics and Communication Technology (IJ-ICT) Vol 9, No 3: December 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (657.26 KB) | DOI: 10.11591/ijict.v9i3.pp157-170

Abstract

Feature selection problem is one of the main important problems in the text and data mining domain. This paper presents a comparative study of feature selection methods for Arabic text classification. Five of the feature selection methods were selected: ICHI square, CHI square, Information Gain, Mutual Information and Wrapper. It was tested with five classification algorithms: Bayes Net, Naive Bayes, Random Forest, Decision Tree and Artificial Neural Networks. In addition, Data Collection was used in Arabic consisting of 9055 documents, which were compared by four criteria: Precision, Recall, F-measure and Time to build model. The results showed that the improved ICHI feature selection got almost all the best results in comparison with other methods.
Co-Authors Laith Abualigah Mohammed A. Otair