3 citations · 5 across the 4 of their papers we have counts for
4 papers · 1 filter
Simplifying Random Forests: On the Trade-off between Interpretability and Accuracy
Michael Rapp, Eneldo Loza Mencía, Johannes Fürnkranz
We analyze the trade-off between model complexity and accuracy for random forests by breaking the trees up into individual classification rules and selecting a subset of them. We s…
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…
On the Trade-off Between Consistency and Coverage in Multi-label Rule Learning Heuristics
Michael Rapp, Eneldo Loza Mencía, Johannes Fürnkranz
Recently, several authors have advocated the use of rule learning algorithms to model multi-label data, as rules are interpretable and can be comprehended, analyzed, or qualitative…
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…