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New to ML in general and have been Googling on this. I am working on a dataset that will rate each customer features to a credit worthiness class attribute.

Is it possible to add class weights in the 'mlp()' function to deal with imbalance of class attributes? I have read the official document for RSNNS package. There is a parameter that is initFunc = "Randomized_Weight" but the documentation does not offer any other initFunc options.

Can this be done on the mlp() parameters, or I have to do a class weightage before the mlp() step?

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