I'm still working to understand estimation of distribution algorithms (EDA) as applied to genetic algorithms. Can the probabilistic models used by EDA for generating new solutions be used by itself? For example, in Bayesian optimization algorithms (BOA) can the Bayesian network that is produced be extracted and used separately as a Bayesian classifier?
R.M. Kapila Tharanga Rathnayaka
This is a good reference for your problem..
https://books.google.lk/books?id=p7ZrlcnvmjUC&pg=PA194&lpg=PA194&dq=Can+the+probabilistic+models+used+in+EDA+be+used+elsewhere?&source=bl&ots=RDYJrEpv14&sig=77RrtSp5q6adhRxBsK3ydZ07JWU&hl=en&sa=X&ved=0ahUKEwiC15On9qnUAhWHvI8KHTp3CbsQ6AEIJjAC#v=onepage&q=Can%20the%20probabilistic%20models%20used%20in%20EDA%20be%20used%20elsewhere%3F&f=false
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