SDDSMOTE: Synthetic Minority Oversampling Technique based on Sample Density Distribution for Enhanced Classification on Imbalanced Microarray Data

Qikang Wan, Xiongshi Deng, Min Li, Haotian Yang. SDDSMOTE: Synthetic Minority Oversampling Technique based on Sample Density Distribution for Enhanced Classification on Imbalanced Microarray Data. In ICCDA 2022: The 6th International Conference on Compute and Data Analysis, Virtual Event / Shanghai China, February 25 - 27, 2022. pages 35-42, ACM, 2022. [doi]

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