AUTOMATED EARLY ANOMALY DETECTION IN A CONTINUOUS LEARNING MODEL

摘要

Embodiments of the present invention provide a method, system and computer program product for automated early anomaly detection in a continuous learning model. In an embodiment of the invention, a method includes training a continuous learning model with a training data set of different records and a known target class for each of the different records, deploying the model, and monitoring performance of the model. The method further includes prior to receiving a complete feedback data set for the model, computing a metric in the model based upon unseen records in the model that had not been present in the training data set, determining poor quality of the model for a metric computed to exceed a threshold value and displaying a recommendation in the host server to retrain the model responsive to the determination of poor quality of the model.