I need a step by step procedure of implementing Bayesian Network for two large dataset to predict interactions (that is patterns and associations).
Also need the breakdown of the Bayesian network machine learning approach to the form that is suitable for coding.
Dear Madam
Pls, see our paper of risk analysis by Bayesian Network.
https://www.researchgate.net/publication/265592739_Impact_of_Risk_Factors_in_Risk_Management_by_Bayesian_Learning
https://users.math.yale.edu/.../CPSC445%20-%20Topic%2006%20-%20Bayesian%20Classifi...
https://software.ucv.ro/~cmihaescu/ro/teaching/AIR/docs/Lab4-NaiveBayes.pdf
https://robotics.stanford.edu/~ronnyk/bayesHB.pdf
https://www.inf.ed.ac.uk/teaching/courses/dme/.../ClassifiersFromBayesianNetworks.pdf
Article Impact of Risk Factors in Risk Management by Bayesian Learning
Hi Jumoke,
I do not know how it is your basis into Bayesian inference, but you can fit easily Bayesian networks using the open-source software "rstan" (it is a probabilistic programming language implemented in a R package). I used to fit several complex Bayesian networks in this software. There are a lot of probabilities distributions to play with. I could even evaluate multivariate Bayesian networks in this programming environment (assuming multivariate normal priors).
I hope to be helpful,
Jhonathan and Bahadorreza,
I do really appreciate your contributions. I will look into the suggestions offered.
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