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In machine learning, a probabilistic classifier is a classifier that is able to predict, given an observation of an input, a probability distribution over a set of classes, rather than only outputting the most likely class that the observation should belong to. Probabilistic classifiers provide classification that can be useful in its own right[1] or when combining classifiers into ensembles.
[I]n data mining applications the interest is often more in the class probabilities themselves, rather than in performing a class assignment.