Posterior Adaptation With New Priors. (arXiv:2007.01386v4 [cs.LG] UPDATED)

Web: http://arxiv.org/abs/2007.01386

Classification approaches based on the direct estimation and analysis of
posterior probabilities will degrade if the original class priors begin to
change. We prove that a unique (up to scale) solution is possible to recover
the data likelihoods for a test example from its original class posteriors and
dataset priors. Given the recovered likelihoods and a set of new priors, the
posteriors can be re-computed using Bayes' Rule to reflect the influence of the
new priors. The method is simple …

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