Neighbor cleaning learning based cost‐sensitive ensemble learning approach for software defect prediction
Li Li,
Renjia Su,
Xin Zhao
Abstract:SummaryThe class imbalance problem in software defect prediction datasets leads to prediction results that are biased toward the majority class, and the class overlap problem leads to fuzzy boundaries for classification decisions, both of which affect the model's prediction performance on the dataset. A neighbor cleaning learning (NCL) is an effective technique for defect prediction. To solve the class overlap problem and class imbalance problem, the NCL‐based cost‐sensitive ensemble learning approach for soft… Show more
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