3 papers
cs.LG2020
Learning Gradient Boosted Multi-label Classification Rules
Michael Rapp, Eneldo Loza Mencía, Johannes Fürnkranz +2
In multi-label classification, where the evaluation of predictions is less straightforward than in single-label classification, various meaningful, though different, loss functions…
cs.LG2019
Efficient Discovery of Expressive Multi-label Rules using Relaxed Pruning
Yannik Klein, Michael Rapp, Eneldo Loza Mencía
Being able to model correlations between labels is considered crucial in multi-label classification. Rule-based models enable to expose such dependencies, e.g., implications, subsu…
cs.LG2019
Improving Outbreak Detection with Stacking of Statistical Surveillance Methods
Moritz Kulessa, Eneldo Loza Mencía, Johannes Fürnkranz
Epidemiologists use a variety of statistical algorithms for the early detection of outbreaks. The practical usefulness of such methods highly depends on the trade-off between the d…