Unbalanced data classification based on oversampling and integrated learning

2021 Asia-Pacific Conference on Communications Technology and Computer Science (ACCTCS)（2021）

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摘要

A lot of unbalanced data exist in the real world, but most of traditional classification algorithms assume that the data is balanced and the misclassification cost is the same with all classes. Therefore, traditional classification algorithm should be modified. This paper proposed an improved unbalanced data classification algorithm: WSMOTEBoost which based on SMOTE and AdaBoost integrated learnin...

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关键词

imbalanced data,integrated learning,cost-sensitive learning,AdaBoost,oversampling

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