Optimal selection of resampling methods for imbalanced data with high complexity.

ABSTRACT: Class imbalance is a major problem in classification, wherein the decision boundary is easily biased toward the majority class. A data-level solution (resampling) is one possible solution to this problem. However, several studies have shown that resampling methods can deteriorate the classification performance. This is because of the overgeneralization problem, which occurs when samples produced by the oversampling technique that should be represented in the minority class domain are introduced into the majority-class domain. This study shows that the overgeneralization problem is aggravated in complex data settings and introduces two alternate approaches to mitigate it. The first approach involves incorporating a filtering method into oversampling. The second approach is to apply undersam

SUBMITTER: Kim A 

PROVIDER: S-EPMC10374143 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature