Are we fitting data or noise? Analysing the predictive power of commonly used datasets in drug-, materials-, and molecular-discovery

We derive maximum and realistic performance bounds based on experimental errors for commonly used machine learning (ML) datasets for regression and classification and compare them to the reported performance of ML models.