Active learning drift analysis and training

Abstract

One or more systems, devices, computer program products and/or computer-implemented methods of use provided herein relate to training a learning model based on determined drift. A system can comprise a memory that stores computer executable components, and a processor that executes the computer executable components stored in the memory, wherein the computer executable components can comprise a selection component that can select an ensemble of deep learning regressors, and an identification component that can identify drift among the ensemble. An analysis component can analyze uncertainty samplings from the ensemble to determine a time instant when drift occurred. A training component can train one or more deep learning models, such as of the deep learning regressors, based upon the identified drift.