medium10 pts · first answer countsimbalanced-datamodel-evaluation

Handling class imbalance

You train a churn classifier where only 5% of users churn. Which approach is a sound first step?

A.Delete all churned users so the model is not confusedB.Use class weights (or resampling on the training set only) and tune the decision threshold on validation dataC.Oversample the minority class before splitting into train and testD.Report accuracy and stop there

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Handling class imbalance

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