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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.

^ Hastie, Trevor; Tibshirani, Robert; Friedman, Jerome (2009). The Elements of Statistical Learning. p. 348. Archived from the original on 2015-01-26. [I]n data mining applications the interest is often more in the class probabilities $p_{\ell }(x),\ell =1,\dots ,K$ themselves, rather than in performing a class assignment.