Computer system and method for determining a cause of an anomaly event for a network device

A computing system for training a machine-learning (ML) model for determining a cause of a detected anomaly event for at least one network device, comprising:

• one or more processors;
• and
• one or more computer-readable media having stored thereon computer-executable instructions that are structured such that, when executed by the one or more processors, cause the computing system to perform at least:
• access a training dataset including a plurality of anomaly events for a plurality of network devices;
• access a training dataset including a plurality of computer network events associated with one or more computer networks the plurality of network devices can be coupled to;
• determine an appearance frequency a certain anomaly event for a network device occurs within a defined time period a network event occurs based upon analysis of data present in the accessed training datasets;
• and
• determine a probability a certain anomaly event for a network device is associated with a network event responsive to the determined appearance frequency, wherein:
• when the machine-learning model is executed, the machine-learning model is configured to determine likelihood a given anomaly event for a network device is caused by a given network event responsive to the probability determination.