A Bayesian belief network uses layers of data and established probability to make decisions. Once the Bayesian network has been provided with all possibilities, and a probability value has been assigned to each possibility, it is possible to infer the most likely outcome. While the complex mathematical calculations necessary to reach these conclusions manually are difficult for anyone who is not a mathematical genius to understand, the underlying principles of a Bayesian probability calculation are relatively simple.
Bayesian Probability Calculations
Bayesian probability networks make decisions based on several layers of data, which can be in a dependent or independent arrangement. Dependent variables change based on other data, while independent variables remain the same regardless of the other input.