Meta-learning model training based on causal transportability between datasets

Abstract

In an embodiment, multiple datasets related to multiple application domains are received. Further, feature dependency information associated with a first dataset is determined, based on a first user input. Also, feature difference information associated with the first dataset and a second dataset is determined, based on a second user input and a set of ethical requirements. A set of structural causal models (SCMs) associated with the first dataset are determined based on the feature dependency information and the feature difference information. A set of ethical coefficients associated with the set of ethical requirements are determined based on an application of a causal transportability model on the set of SCMs. A trust score associated with the first dataset is determined based on the set of ethical coefficients. The trust score is used to train a meta-learning model associated with the multiple application domains.