Hello all,
Is there any algorithms of Bayesian Network to work directly on the
mixture of continuous and categorical variables?
The classification problem that I am working on has 37 input variables, 15
of them are categorical and the rest of them are continuous. To my
understanding, I need to discretize the continuous varibles in order to
apply some commonly used algorithms (such as junction tree) to construct
and estimate BNs. Since a large portion of the input variables are
continuous, I am afraid of loss of information by discretizing them.
References and input on working directly on the mixture will
be highly appreciated. I would also like to have any comments and
experiences on how much gain we can get from working on the mixture
directly over transforming all variables into discrete. Thanks.
Best regards,
Julie
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