Output posterior distribution from bayesian network in R (bnlearn)

Question

I'm experimenting with Bayesian networks in R and have built some networks using the bnlearn package. I can use them to make predictions for new observations with predict(), however I would also like to have the posterior distribution over the possible classes. Is there a way of retrieving this information?

It seems like there is a prob-parameter that does this for the naive bayes implementation in the bnlearn package, but not for networks fitted with bn.fit.

Thankful for any help with this.

Answer 1

See the documentation of bnlearn. predict function implements prob only for naive.bayes and TAN.

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In short, because all other methods do not necessarily compute posterior probabilities.

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[bnlearn] :: predict returns the predicted values for node given the data specified by data. Depending on the value of method, the predicted values are computed as follows: a)parents b)bayes-lw When using bayes-lw , likelihood weighting simulations are performed for making predictions.

Hope this helps. :)