Dear Support team,
I am following the PDF version of the tutorial for SMILE wrappers, specifically for the Python language.
Is there a way to output goodness-of-fit metric such as BIC, log likelihood score, given a predefined network structure and a dataset?
BIC score (Bayesian Information Criterion): the scoring functions in probabilistic graphical models and Bayesian networks after the EM (Expectation-Maximization) parameter estimation step.
Thank you very much for your answer.
is there a way to output goodness-of-fit metric such as BIC, log likelihood score?
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Re: is there a way to output goodness-of-fit metric such as BIC, log likelihood score?
You can obtain the log likelihood after EM by calling the EM.get_last_score() method.
BayesianSearch.get_last_score() returns the Bayesian score after learning.
Currently there's no method to calculate BIC from the dataset and network without learning.
BayesianSearch.get_last_score() returns the Bayesian score after learning.
Currently there's no method to calculate BIC from the dataset and network without learning.
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Re: is there a way to output goodness-of-fit metric such as BIC, log likelihood score?
BTW, you can use GeNIe to calculate loglikelihood for a dataset/network without learning. This functionality is not exposed in PySMILE, however.
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Re: is there a way to output goodness-of-fit metric such as BIC, log likelihood score?
One more thing, we're now working on additional structure learning algorithms and there will be a way to calculate BIC for network+dataset directly.