Base Station Anomaly Prediction Leveraging Model-Driven Framework for Classification in Neo4j

Machine learning is one of key-enablers in case of novel usage scenarios and adaptive behavior within next generation mobile networks. In this paper, it is examined how model-driven approach can be adopted to automatize machine learning tasks aiming mobile network data analysis. The framework is evaluated on classification task for purpose of base station anomaly detection relying on Neo4j graph database. According to the experiments performed …