Data processing system and method for acquiring data for training a machine learning model for use in monitoring the data processing system for anomalies

A data processing system and a method are provided for acquiring data for training a machine learning (ML) model for use in self-monitoring the data processing system. The data processing system operates in a data acquisition mode to acquire training data for training the ML model. The training data is acquired from an anomaly detector of the data processing system while operating in the data acquisition mode. At least a portion of the training data is determined to be biased, and a portion of the training data is unbiased. The unbiased portion of the training data is transferred to a training environment external to the data processing system. The unbiased portion of the training data is acquired for training the ML model to function with the anomaly detector during a normal operating mode to determine when an anomaly is present in the data processing system.