Systems and methods for detecting data drift for data used in machine learning models

摘要

A system and method for detecting data drift is disclosed. The system may be configured to perform a method, the method including receiving model training data and generating a predictive model. Generating the predictive model may include model training or hyperparameter tuning. The method may include receiving model input data and generating predicted data using the predictive model, based on the model input data. The method may include receiving event data and detecting data drift based on the predicted data and the event data. The method may include receiving current data and detecting data drift based on the data profile of the current data. The method may include model training and detecting data drift based on a difference in a trained model parameter from a baseline model parameter. The method may include hyperparameter tuning and detecting data drift based on a difference in a tuned hyperparameter from a baseline hyperparameter. The method may include correcting the model based on the detected data drift.