Development and implementation of methodology for intellectual data analysis using Bayesian networks theory and regression analysis
A new two-stage method for intellectual data analysis is proposed that combines Bayesian networks theory and regression analysis. The method is based on two sets of mathematical techniques. The first one is used for constructing topology of Bayesian network and forming probabilistic inference. The inference is used further on for decision making on the basis of forecast estimates. The second set of methods is used for development of regression model with making use of logistic link function that serves as a basis for forecast estimation.