On the efficient implementation of classification rule learning
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Publication:6661121
DOI10.1007/S11634-023-00553-7MaRDI QIDQ6661121
Michael Rapp, Johannes Fürnkranz, Eyke Hüllermeier
Publication date: 12 January 2025
Published in: Advances in Data Analysis and Classification. ADAC (Search for Journal in Brave)
parallelizationclassification rulesmulti-label classificationgradient boostinglarge-scale machine learning
Cites Work
- Title not available (Why is that?)
- Predictive learning via rule ensembles
- On label dependence and loss minimization in multi-label classification
- Separate-and-conquer rule learning
- Rule-based multi-label classification: challenges and opportunities
- Editable machine learning models? A rule-based framework for user studies of explainability
- Isotonic boosting classification rules
- SIRUS: stable and interpretable RUle set for classification
- Foundations of Rule Learning
- LAPACK Users' Guide
- Definitions, methods, and applications in interpretable machine learning
- An updated set of basic linear algebra subprograms (BLAS)
- Random forests
- Is there a role for statistics in artificial intelligence?
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