Adobe Inc.
METHODS AND SYSTEMS FOR DETECTION AND ISOLATION OF BIAS IN PREDICTIVE MODELS

Abstract:

This disclosure involves detecting biases in predictive models and the root cause of those biases. For example, a processing device receives test data and training data from a client device. The processing device identifies feature groups from the training data and the test data generates performance metrics and baseline metrics for a feature group. The processing device detects biases through a comparison of the performance metrics and the baseline metrics the feature group. The processing device then isolates a portion of the training data that corresponds to the detected bias. The processing device generates a model correction usable to remove the bias from the predictive model.