While "standard" answers to these questions exist, it is rarely clear if and in what sense they are optimal or even admissible for the prediction task at hand. In the first part of the talk, we will consider three relevant and concrete examples of such questions related to model evaluation. Furthermore, we will illustrate how the derivation of more appropriate (than "standard") answers is in principle possible based on recent methodological work.

However, finding problem-tailored solutions in the scientific literature can also be difficult and time-consuming, in particular for practitioners whitout a specific data science background. In the second part of the talk, I will therefore introduce the expert system mIguide which is currently under active development at Fraunhofer MEVIS. mlguide aims to provide interactive support to practitioners for solving methodological questions in applied machine learning problems, such a those mentioned before. I will illustrate the overall system architecture, some insights into the guidance engine, and current limitations. To conclude, I will give an outlook on planned features and user research.

Kontakt: Sekretariat IMBE, Institut für Biometrie und Epidemiologie, Tel.: 040 7410 59551 , Mail: imbe-sekretariat@uke.de