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Hi folks,
Can anyone explain me about how to determine the
priori probabilities when Bayesian decision rule is applied, say, to classify a
pattern into object class and non-object class? I know usually equal priori is
assumed, but in this case how can the training set for both classes be
interpreted? I mean, are these priori probabilities not necessarily derived
from the training set since usually in which postive samples are not equal to
negative samples? Any help will be greatly appreciated.
Many Thanks.
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- Interpret H�dia Mhiri Sellami
- Re: priori probs qhwang
- Re: priori probs Gilles CARAUX
- Re: priori probs QingHua Wang
