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Are two Classifiers performing equally? A treatment using Bayesian Hypothesis Testing
Barber, David
2004
We consider here how to assess if two classifiers, based on a set of test error results, are performing equally well. This question is often considered in the realm of sampling theory, based on classical hypothesis testing. Here we present a simple Bayesian treatment that is quite general, and also is able to deal with the (practically common) case where the errors that two classifiers make are dependent.
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barber_dirichlet_test_idiap_rr.pdf
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openaccess
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321 B
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