CCR: A combined cleaning and resampling algorithm for imbalanced data classification - Koziarski, Michał; Woźniak, Michał (Zielona Góra: Uniwersytet Zielonogórski)
Imbalanced data classification is one of the most widespread challenges in contemporary pattern recognition. Varying levels of imbalance may be observed in most real datasets, affecting the performance of classification algorithms. Particularly, high levels of imbalance make serious difficulties, often requiring the use of specially designed methods. In such cases the most important issue is often to properly detect minority examples, but at the same time the performance on the majority class cannot be neglected.
Keywords: machine learning; classification; imbalanced data; preprocessing; oversampling