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Michael Rapp
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Learning Gradient Boosted Multi-label Classification Rules
M Rapp, E Loza Mencía, J Fürnkranz, VL Nguyen, E Hüllermeier
European Conference on Machine Learning and Knowledge Discovery in Databases …, 2020
302020
On aggregation in ensembles of multilabel classifiers
VL Nguyen, E Hüllermeier, M Rapp, E Loza Mencía, J Fürnkranz
Discovery Science: 23rd International Conference, DS 2020, Thessaloniki …, 2020
132020
Rule-based multi-label classification: Challenges and opportunities
E Hüllermeier, J Fürnkranz, E Loza Mencia, VL Nguyen, M Rapp
Rules and Reasoning: 4th International Joint Conference, RuleML+ RR 2020 …, 2020
122020
Learning Interpretable Rules for Multi-label Classification
E Loza Mencía, J Fürnkranz, E Hüllermeier, M Rapp
Explainable and Interpretable Models in Computer Vision and Machine Learning …, 2018
112018
Gradient-based Label Binning in Multi-label Classification
M Rapp, E Loza Mencía, J Fürnkranz, E Hüllermeier
European Conference on Machine Learning and Knowledge Discovery in Databases …, 2021
92021
BOOMER—An algorithm for learning gradient boosted multi-label classification rules
M Rapp
Software Impacts 10, 100137, 2021
82021
A flexible class of dependence-aware multi-label loss functions
E Hüllermeier, M Wever, E Loza Mencia, J Fürnkranz, M Rapp
Machine Learning 111 (2), 713-737, 2022
52022
Efficient discovery of expressive multi-label rules using relaxed pruning
Y Klein, M Rapp, E Loza Mencía
Discovery Science: 22nd International Conference, DS 2019, Split, Croatia …, 2019
52019
Exploiting anti-monotonicity of multi-label evaluation measures for inducing multi-label rules
M Rapp, E Loza Mencía, J Fürnkranz
Advances in Knowledge Discovery and Data Mining: 22nd Pacific-Asia …, 2018
52018
Learning Structured Declarative Rule Sets--A Challenge for Deep Discrete Learning
J Fürnkranz, E Hüllermeier, EL Mencía, M Rapp
arXiv preprint arXiv:2012.04377, 2020
42020
Simplifying Random Forests: On the Trade-off between Interpretability and Accuracy
M Rapp, EL Mencía, J Fürnkranz
arXiv preprint arXiv:1911.04393, 2019
42019
Correlation-Based Discovery of Disease Patterns for Syndromic Surveillance
M Rapp, M Kulessa, E Loza Mencía, J Fürnkranz
Frontiers in Big Data 4, 2022
32022
On the trade-off between consistency and coverage in multi-label rule learning heuristics
M Rapp, E Loza Mencía, J Fürnkranz
Discovery Science: 22nd International Conference, DS 2019, Split, Croatia …, 2019
22019
On the efficient implementation of classification rule learning
M Rapp, J Fürnkranz, E Hüllermeier
Advances in Data Analysis and Classification, 1-42, 2023
2023
Multi-label Rule Learning
M Rapp
Technische Universität Darmstadt, 2022
2022
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