221 citations · 264 across the 14 of their papers we have counts for
17 papers
Combining Predictions under Uncertainty: The Case of Random Decision Trees
Florian Busch, Moritz Kulessa, Eneldo Loza Mencía +1
A common approach to aggregate classification estimates in an ensemble of decision trees is to either use voting or to average the probabilities for each class. The latter takes un…
Correlation-based Discovery of Disease Patterns for Syndromic Surveillance
Michael Rapp, Moritz Kulessa, Eneldo Loza Mencía +1
Early outbreak detection is a key aspect in the containment of infectious diseases, as it enables the identification and isolation of infected individuals before the disease can sp…
Gradient-based Label Binning in Multi-label Classification
Michael Rapp, Eneldo Loza Mencía, Johannes Fürnkranz +1
In multi-label classification, where a single example may be associated with several class labels at the same time, the ability to model dependencies between labels is considered c…
Revisiting Non-Specific Syndromic Surveillance
Moritz Kulessa, Eneldo Loza Mencía, Johannes Fürnkranz
Infectious disease surveillance is of great importance for the prevention of major outbreaks. Syndromic surveillance aims at developing algorithms which can detect outbreaks as ear…
Learning Structured Declarative Rule Sets -- A Challenge for Deep Discrete Learning
Johannes Fürnkranz, Eyke Hüllermeier, Eneldo Loza Mencía +1
Arguably the key reason for the success of deep neural networks is their ability to autonomously form non-linear combinations of the input features, which can be used in subsequent…
A Flexible Class of Dependence-aware Multi-Label Loss Functions
Eyke Hüllermeier, Marcel Wever, Eneldo Loza Mencia +2
Multi-label classification is the task of assigning a subset of labels to a given query instance. For evaluating such predictions, the set of predicted labels needs to be compared…