Algebraic Bayesian Networks: Naïve Frequentist Approach to Local Machine Learning Based on Imperfect Information from Social Media and Expert Estimates

Abstract

The task of model learning arises in algebraic Bayesian networks as one of the probabilistic graphical models. Several approaches to machine learning of algebraic Bayesian networks are known. This research is dedicated to the algorithm of machine learning of algebraic Bayesian network represented by a knowledge pattern on missing data. Besides this algorithm, some examples of machine learning on artificial and real data from social media are considered.