Survey of resampling techniques for improving classification performance in unbalanced datasets

2016/08/22 by More, Ajinkya · 1 citation
#Applications (stat.AP) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)

paper · doi:10.48550/arxiv.1608.06048

Abstract

A number of classification problems need to deal with data imbalance between classes. Often it is desired to have a high recall on the minority class while maintaining a high precision on the majority class. In this paper, we review a number of resampling techniques proposed in literature to handle unbalanced datasets and study their effect on classification performance.

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