John Mount warns against simply returning a class in a classification problem:
This statement is a bit of word-play which I will need to unroll a bit. However, the concrete advice is that you often get better results using models that return a continuous score for classification problems. You should make that numeric score available to downstream business logic instead of making a class choice at model prediction time. Informally the word “classifier” to informally mean “scoring procedure for classes” is not that harmful. Losing a numeric score is harmful.
Read the whole thing, as John lays out a good argument.