I have a binary classification problem and two sets of features(for the same target variable) . Due to some reason(domain knowledge), I can't combine those two feature sets into one and then do classification. The only option is two build two different classifiers (for the same target variable) on the individual feature sets. Now if a new data comes in, I will have predictions from both of these models. How do I combine the two predictions?

P.S: I was thinking of a logistic regression model that will take my predictions and assign weights to each of them. Now using the target y, I will learn those weights.


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