Techniques for training a generative relational network

Abstract

A system and method for training relational networks. A method includes applying a self-organizing map (SOM) to training data in order to create a visualization. The SOM is a neural network configured to transform relationships between data items. The visualization has a lower dimensionality than the training data. The method also includes training machine learning models of a generative relational network (GRN) based on the visualization, where the GRN includes sets of nodes having respective machine learning models among the machine learning models of the GRN and the sets of nodes include a set of dominance factor nodes and a set of evolution of internal component nodes. The set of dominance factor nodes defines a dominance factor based on change intensity and change frequency, and the set of evolution of internal component nodes defines evolution with respect to changes determined based on values of the dominance factor over time.