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I have a rather imbalanced (5% positive values), conversion dataset that I'm trying to use the new ML tools to predict the conversion targets.
Traditionally, I would oversample the dataset to balance the target variable, but the assisted modelling doesnt appear to balance the target and just predicts everything as negative for very high accuracy.
Does the assisted modelling have any way of treating or managing imbalanced datasets for classification at all?
Hey @DavidSta so I understand using the predict rather than the score tool for the ML tools. In my example the imbalance is 95%-5% does this mean that the existing tools would not be able to address this imbalance (even using the oversampling as mentioned) as there is no way to account for that adjustment and there for account for that adjustment?