Bug Severity Prediction using Class Imbalance Problem
Shubhra Goyal Jindal*,
Arvinder Kaur
Abstract:Class imbalance problem is often observed when instances of major class exceed instances of minor class. The performance of machine learning techniques is immensely afflicted by imbalanced data in several fields. The skewed distribution either predicts the majority class with high error rate or will not foresee the minority class. To solve the problem of imbalanced data of software bugs, Synthetic minority oversampling technique (SMOTE) is used which balances the imbalanced datasets of Apache Projects. It is a… Show more
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