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I found on the forum that in order to compensate for an unbalanced class/skewed class distribution one should use the 'EqualLabelWeighting' operator. So I loaded the data using a csv file and the 'ExampleSource' operator making the skewed column the label with the attribute wizard, added the 'EqualLabelWeighting' operator and hit play...It appears to have added a weight column and the weights appear to be appropriate to balance the column...what next.
I wanted to use a learner (like a DecisionTree) next but now the label is assigned to the wrong column...how do I change the label back to the variable I'm trying to predict for? Is this even the right way to use the operator?
I'm lost...any help would be appreciated.