RACOG and wRACOG: Two Probabilistic Oversampling Techniques

Volume: 27, Issue: 1, Pages: 222 - 234
Published: Jan 1, 2015
Abstract
As machine learning techniques mature and are used to tackle complex scientific problems, challenges arise such as the imbalanced class distribution problem, where one of the target class labels is under-represented in comparison with other classes. Existing oversampling approaches for addressing this problem typically do not consider the probability distribution of the minority class while synthetically generating new samples. As a result, the...
Paper Details
Title
RACOG and wRACOG: Two Probabilistic Oversampling Techniques
Published Date
Jan 1, 2015
Volume
27
Issue
1
Pages
222 - 234
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