Sorry if you receive duplicated copies for this mail. I wonder there is
something wrong since I don't receive the mail I sent to the maillisting
in this morning.
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Many thanks for your pointer. I will find whether there is such a book
in our library.
On Wed, 2003-06-25 at 07:53, Gilles CARAUX wrote:
> If prior probabilities are unknown, I suggest MinMax rule as described in Hand
> (1981) page 7.
> The Bayesian decision rule, in MinMax approach, is designed so that we minimize the
> maximum possible risk.
>
> Hand, D. J. (1981), Discrimination and Classification, John Wiley.
>
>
> A 21:29 23/06/2003, qhwang a �crit :
> >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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