As an important by-product of our study, we provide empirical insights into the importance of inclusion criteria for datasets in benchmarking experiments and general critical discussions on design issues and scientific practice in this context. The goal of our paper is thus two-fold. Firstly we aim to present solid evidence on the performance of standard logistic regression and random forests with default values. Secondly, we demonstrate the design of a benchmark experiment inspired from clinical trial methodology.
