Probabilistic classification: Difference between revisions

Revision as of 14:19, 1 April 2018

Revision as of 10:08, 29 May 2018

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==Evaluating probabilistic classification==

Commonly used loss functions for probabilistic classification include [[log loss]] and the [[meanBrier squared errorscore]] 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]].