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Dealing with Imbalanced Data
This is what I need to do, but I'm stuck:
1) Take the original dataset
2) Split it according to the value of the label (call the two new example sets : Common and Rare).
3) Resample (bootstrap) the Rare ExampleSet until it has the same size as the Common ExampleSet.
4) Join the resampled Rare with the old Common.
I can do it outside Rapid-I, but I was wondering if it can be done with a few operators.
Thanks in advance for any help,