A Guidline for Creating Assessments in Machine Learning Education

Even though machine learning field is growing rapidly, research on education of machine learning is scarce. In this paper a research about creating assessments in the machine learning’s context is presented. The aim of the research is to answer how to design assessments that reliably show progress on a module in machine learning. Learning...

Towards Explaining Automated Credit Decisions: The design of an Explicability Assessment Framework (EAF) for Machine Learning Systems

The use of machine learning systems has great potential to better predict probabilities of default for credit underwriting. Despite this advantage, herewith there exists the substantial risk of discrimination. Moreover, machine learning models with the highest prediction-accuracy are often the least explicable (i.e. explainable). Nonetheless,...