Dataset shift will lead to uncertainty issues, and then the models will accurately decline. Using causality instead of correlation to find the invariant characteristic and solve the uncertainty issues between different dataset distributions (eg. Domain Adaptation). Summarizing datasets can be used in current domain training, building a benchmarking framework of causal learning that combines the causal inference and traditional model to detect, address, and determine the characteristic of the dataset shift.