What prior does scikit-learn use for MultinomialNB? The documentation says:
*class_prior : array-like, size (n_classes,)*
*Prior probabilities of the classes. If specified the priors are not
adjusted according to the data.*
For N classes, one typically uses a Dirichlet prior
<http://en.wikipedia.org/wiki/Dirichlet_distribution>, but this prior would
be specified with N positive values (for the concentration parameters), not
with N probabilities (quantities bounded between 0 and 1). So MultinomialNB
seems to be using something different. What is it?
Josh
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