Could you be a little more specific? Do you mean
a priori probabilities? Are you referring to the chance probabilities of an object belonging to a particular class or not belonging to that class? What do you mean by a "training set"? Can you give an example of a specific problem in terms of number of objects (entities, etc.) to be classified; number and type of variates from which a pattern is derived; type of values assigned to the variates, etc.
M. Childress
>From: qhwang <[EMAIL PROTECTED]>
>Reply-To: "Classification, clustering, and phylogeny estimation" <[EMAIL PROTECTED]>
>To: [EMAIL PROTECTED]
>Subject: priori probs
>Date: Mon, 23 Jun 2003 20:29:43 +0100
>
>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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