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Class imbalance handling using wrapper-based random oversampling
Year: 2012
Abstract:
We propose a novel algorithm for handling class imbalance. Class imbalance is a problem occurring in some valuable data such as medical diagnosis, fraud detection, oil spills, etc. The problem influences all supervised ...