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Does anyone know how to learn some of the parameters in a DBN and freeze the rest of them - In case if I have those parameters a priori?
For example in the HMM learning problem:
X0 -> X1
, what if I already have the observation probability distribution P( Y | X ) and just need to learn the state transition probability function P ( X' | X ) from the evidences?