Methods, systems and computer readable media for predicting risk in network elements using machine learning

Abstract

A method, system and computer-readable medium where a weighted composite quality index having a plurality of components for a network element is identified. A historical baseline value from historical data for each component is determined, and a deviation from the historical baseline values is measured. A risk level for the deviation is assigned. A loss score for the measured components is computed by mapping the risk level to a numerical score. An aggregated risk score based on a sum of weighted risk scores for each of the components is computed. An expected risk score based on probabilities associated with the aggregated risk score is determined by computing future probabilities of each risk level at the network element based on a trained machine learning model.