A Bayes classifier is a classification rule that applies the Bayes decision rule. Given probabilities under a posterior distribution for classes , ..., and a loss function , where is the numerical penalty for choosing action when the true class is , the Bayes classifier chooses an action that minimizes the posterior expected loss

For a zero-one loss function, this is equivalent to choosing the class having largest such probability,

See also

Bayes Decision Rule, Classification, Loss Function, Pattern Recognition, Posterior Distribution

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References

Bishop, C. M. Pattern Recognition and Machine Learning. New York: Springer, 2006.

Cite this as:

Weisstein, Eric W. "Bayes Classifier." From MathWorld--A Wolfram Resource. https://mathworld.wolfram.com/BayesClassifier.html

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