| 15 | 15 | Different scientific articles have been produced on this topic. One of those articles presents a 'decision tree' that can, and is, used by doctors to predict risk on (pre-)diabetes. Reproducing this decision tree is the first step in this project. As a next step you will come up with a criterion that indicates the performance of a given decision tree. Next, you will optimise that criterion as function of the cut-offs in the tree. We challenge you to come up with an even better decision tree. Do you realise that information may be lost each time the tree branches? Maybe you can come up with a model that does not have this drawback? You will also answer questions about the reproducibility of your research. To what extend are your finding generalisable from one data set to another one? |
