Validity, Reliability, and Significance

Addresses methodological questions that include the problems of validity, reliability, and significance. In the case of machine learning, these correspond to whether a model predicts what it purports to predict, whether its performance is consistent across replications, and whether a performance difference between two models is due to chance.