Marcel Zalmanovici

Detection of data drift and outliers affecting machine learning model performance over time

2020 · arXiv (Cornell University)

A trained ML model is deployed on another `test' dataset where target feature values (labels) are unknown. Drift is distribution change between the training and deployment data, which is concerning if model performance changes. For …