An improved Chi-sqaure feature selection for Arabic text classification using decision tree
Said Bahassine, Abdellah Madani, Mohamed Kissi · 2016
Feature selection is an important and necessary step that can improve greatly the classification performance. The aim of the present paper is to investigate a new feature selection (referred to, hereafter, as ImpCHI), when using light stemming. ImpCHI is an improvement of chi-square - one of the most effective feature selection methods to date. Evaluation used a corpus that consists of 250 Arabic documents independently classified into five classes: art and culture, economics, politics, society, and sport. The experiment results show that Arabic text classification using ImpCHI as feature selection outperforms using chi-square in terms of recall-measures.