This project developed and implemented new techniques for the analysis of survival data.
The key insight is to focus on prognosis, rather than on modelling explicitly the mechanisms underlying the phenomenon.
Hereto, we tune methods of modern machine learning towards this task, resulting in APTER (Aggregated Prognosis Through Exponential Reweighting).
This method is analyzed and benchmarked based on artificial and real data sets.

The results of the project are given on the Survlab website.
The site contains all used software, the experimental results as well as the used data sets.