Approaches to handle class imbalance

Rsampling, Cost Senstive Learning, Ensemble Learning, Smote are various methods to handle class imbalance problem. Class imbalance problem occurs when there is a significant difference in the number of samples in each class of a classification problem. This can lead to a biased model that is more likely to predict the majority class, even when the minority class is the one that is actually of interest.

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Approaches to handle class imbalance

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