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Yue Yan

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Open access Aug 2026

Applying Cost-Sensitive Learning to Mitigate the Effect of Class Imbalance for Deep Learning-based Fault Localization

This work proposes applying cost-sensitive learning to set different weights for each sample to optimize the performance of fault localization and demonstrates that applying cost-sensitive learning can effectively alleviate the class imbalance problem in DLFL.

Yue Yan, Shu-Juan Jiang, Yanmei Zhang et al. · 0 citations

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