Changing Notation: If there are c classes with size Ni (i=1:c), N = sum(i=1,c){Ni}, then the a priori probabilities are Pi = Ni/N ;
With no other information "prior" to making calculations and/or measurements, the Naïve Bayes Classifier will assign all inputs to the class with the maximum prior probability. The corresponding per cent classifier accuracy is 100*max(Pi).
If the classes are the same size, the percent classification accuracy is 100*(1/c) (50% for c=2, 33.3% for c=3, etc)..
Hope this helps.
Thank you for formally accepting my answer
Greg
P.S. I probably have posted details in comp.ai.neural-nets and comp.soft-sys.matlab (and maybe even ANSWERS). Try searching on
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