Probabilistic classification: Difference between revisions

Revision as of 13:13, 14 September 2015

Revision as of 16:31, 21 December 2015

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==Evaluating probabilistic classification==

Commonly used loss functions for probabilistic classification include [[log loss]] and the [[mean squared error]] between the predicted and the true probability distributions. The former of these is commonly used to train logistic models.

A method used to assign scores to pairs of predicted probabilities and actual discrete outcomes, so that different predictive methods can be compared, is called a [[scoring rule]].

==References==