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. >
