SYSTEM AND METHOD FOR IMPROVING MACHINE LEARNING MODEL PERFORMANCE IN A COMMUNICATIONS NETWORK

A system, method and non-transitory computer readable media for optimizing input data for an ML model associated with a communications network. In one implementation, example ML model(s) may be trained using a modified dataset obtained for a plurality of cellular aggregation units (CAUs) of the RAN infrastructure(s), wherein the modified dataset is derived from data collected for individual CAUs over a data collection period with respect to a plurality of KPI variables. The modified data set is optimized by replacement of null values of variables with corresponding modal values of the variables. The trained ML model may be used for predicting one or more KPIs based on a set of test data associated with the RAN infrastructure(s).