Imprecise probabilities offer a rigorous framework to characterise uncertainty when precise numerical probabilities are either unavailable or unwarranted. This concept expands traditional probability ...

Abstract: We present a novel approach for estimating conditional probability tables, based on a joint, rather than independent, estimate of the conditional distributions belonging to the same table.

Answer any query from a joint distribution. Construct joint distribution from conditional probability tables using chain rule. Construct joint distribution from Bayes net and conditional probability ...

Abstract: With the development of information technology, the scope of battlefield is more and more extensive, and multi-domain Defensive operations are getting more and more attention. In order to ...

Conditional probability occurs when it is given that something has happened. (Hint: look for the word “given” in the question. The probability that a tennis player wins the first set of a match is ...

This project is designed to process queries on Bayesian Networks. It allows users to load a Bayesian network from an XML file, perform conditional probability calculations using Variable Elimination, ...

# Update DAG with the CPTs model = bn.make_DAG(DAG, CPD=[cpt_cloudy, cpt_sprinkler, cpt_rain, cpt_wet_grass]) bn.print_CPD(model) ends up with [bnlearn] >No changes ...