My dataset has input_features, continuous_label1 and continuous_label2. I always have data for input_features but occasionally continuous_label1 or continuous_label2 has no value. I don’t want to remove the lines where this is the case because learning can still happen when one of the two values are missing.
My loss function is “MSE loss for continuous_label1” + “MSE loss for continuous_label2”. What is the proper way to handle this situation? One option would be to set the missing value as the prediction. Would that make sense?