Classification of Quranic topics based on imbalanced classification

Imbalanced classification techniques have been applied widely in the field of data mining. It is used to classify imbalanced classes that are not equal number samples. The problem performance tends class with more samples while few will obtain poor performance. This can be occurred Qur’anic due different verses. Many studies classified verses, which depended on traditional classification. However, no study topics based Therefore, this paper aims apply methods as synthetic minority over-sampling technique (SMOTE), random over sample (ROS), and under (RUS) imbalanced. metrics were research evaluate experimental results. These sensitivity/recall, specificity, overall accuracy, F-Measure, G-mean, matthews correlation coefficient (MCC). results showed Quranic improved when