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Grading Cost Sensitive Models

A learner induced from an imbalanced dataset has a low error rate for the majority class and an undesirable error rate for the minority class. This paper provides a study on the various methodologies that have tried to handle this problem. Finally, it presents an experimental study of these methodologies with a proposed grading cost-sensitive ensemble and it concludes that this ensemble is a more effective solution to the problem.