Methods and apparatuses for detecting and localizing faults using machine learning models

Abstract

A method of pre-processing data for use in training one or more machine learning, ML, models for use in detecting anomalies occurring during execution of one or more procedures at a plurality of network nodes in a network, includes: obtaining procedure level time series data relating to the execution of a first procedure at the plurality of network nodes; and deriving, from the procedure level time series data relating to the execution of the first procedure at the plurality of network nodes, one or more first feature time series of one or more respective first feature values, wherein the one or more first feature time series are for use in training a first ML model associated with the first procedure.

CPC Classifications