R Code corresponding to the ISIPTA Project "Depth Functions for Partial Orders with a Descriptive Analysis of Machine Learning Algorithm"

This repository consits of R-Code corresponding the ISIPTA Project "Depth Functions for Partial Orders with a Descriptive Analysis of Machine Learning Algorithm". Here we analyze ML algorithms based on depth functions and give an counterexample to prove Property (P1) of

Hannah Blocher, Georg Schollmeyer, Christoph Jansen and Malte Nalenz (2023): Depth Functions for Partial Orders with a Descriptive Analysis of Machine Learning Algorithms. In: Proceedings of the Thirteenth International Symposium on Imprecise Probabilities: Theories and Applications (ISIPTA '23). Proceedings of Machine Learning Research, vol. 215. PMLR. (see here)

Set up / Files

• Performance_Analysis_ML_Algorithms: Corresponds to Section 6 of the paper.
• Counterexample_for_theorem_7: Counterexample to prove Property (P1), see Theorem 7 in the appendix for further details.