EXPLAINABILITY-BASED ADJUSTMENT OF MACHINE LEARNING MODELS

摘要

An apparatus for explainability-based adjustment of machine learning models includes a first prediction module configured to receive a first set of predictions from a primary machine learning model based on a data set, a second prediction module configured to receive a second set of predictions from a secondary machine learning model based on the data set, and an action module configured to trigger one or more actions related to the primary machine learning model in response to a comparison of the first and second sets of predictions not satisfying one or more explainability criteria.