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449 Publications


2009 | Journal Article | LibreCat-ID: 16158
Hühn J, Hüllermeier E. FURIA: An Algorithm for unordered fuzzy rule induction. Data Mining and Knowledge Discovery . 2009;19:293-319.
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2009 | Journal Article | LibreCat-ID: 16159
Hüllermeier E, Vanderlooy S. Why fuzzy decision trees are good rankers. IEEE Transactions on Fuzzy Systems. 2009;17(6):1233-1244.
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2009 | Journal Article | LibreCat-ID: 16161
Yi Y, Fober T, Hüllermeier E. Fuzzy operator trees for modeling rating functions. International Journal of Computational Intelligence and Applications. 2009;8(4):413-428.
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2009 | Journal Article | LibreCat-ID: 16162
Fober T, Mernberger M, Klebe G, Hüllermeier E. Evolutionary construction of multiple graph alignments for the structural analysis of biomolecules. Bioinformatics. 2009;25(16):2110-2117.
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2009 | Journal Article | LibreCat-ID: 16163
Hühn J, Hüllermeier E. FR3: A fuzzy rule learner for inducing reliable classifiers. IEEE Transactions on Fuzzy Systems. 2009;17(1):138-149.
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2009 | Journal Article | LibreCat-ID: 16165
Hüllermeier E, Vladimirskiy I, Prados Suarez B, Stauch E. Supporting case-based retrieval by similarity skylines: Basic concepts and extensions. Künstliche Intelligenz. 2009;1(09):24-29.
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2009 | Book Chapter | LibreCat-ID: 10188
Hüllermeier E. On the usefulness of fuzzy sets in data mining. In: Seising R, ed. Views on Fuzzy Sets and Systems from Different Perspectives: Philosophy and Logic, Criticisms and Applications. Springer; 2009:457-470.
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2009 | Conference Paper | LibreCat-ID: 13595
Cheng W, Hühn J, Hüllermeier E. Decision tree and instance-based learning for label ranking. In: In Proceedings ICML-2009, 26th International Conference on Machine Learning, Montreal, Canada. ; 2009:161-168.
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2009 | Conference Paper | LibreCat-ID: 13596
Fürnkranz J, Hüllermeier E, Vanderlooy S. Binary decomposition methods for multipartite ranking. In: In Proceedings ECML/PKDD-2009, European Conference on Machine Learning and Principles and Knowledge Discovery in Databases, Bled Sloveniaery in Databases, Bled, Slovenia. ; 2009.
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2009 | Conference Paper | LibreCat-ID: 13598
Cheng W, Hüllermeier E. A new instance-based label ranking approach using the Mallows model. In Advances in Neural Networks. In: In Proceedings 6th International Symposium on Neural Networks, Wuhan, China. Springer; 2009:707-716.
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2008 | Conference Paper | LibreCat-ID: 15779
Hüllermeier E, Vanderlooy S. Weighted voting as approximate MAP prediction in pairwise classification. In: In Proceedings Workshop LWA-2008, Lernen-Wissensentdeckung-Adaptivität, Würzburg, Germany. ; 2008:34-41.
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2008 | Conference Paper | LibreCat-ID: 15780
Fober T, Hüllermeier E, Mernberger M. Evolutionary construction of multiple graph alignments for mining structured biomolecular data . In: In Proceedings Workshop LWA-2008, Lernen-Wissensentdeckung-Adaptivität, Würzburg, Germany. ; 2008:27-33.
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2008 | Conference Paper | LibreCat-ID: 15781
Fober T, Hüllermeier E, Mernberger M. Evolutionary construction of multiple graph alignments for the structural analysis of biomolecules. In: Beyer A, Schroeder M, eds. IIn Proceedings GCB-2008, Germany Conference on Bioinformatics, Dresden 2008. ; 2008:44-53.
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2008 | Journal Article | LibreCat-ID: 16164
Hühn J, Hüllermeier E. Is an ordinal class structure useful in classifier learning? International Journal of Data Mining, Modeling and Management . 2008;1(1):45-67.
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2008 | Journal Article | LibreCat-ID: 16166
Hüllermeier E, Fürnkranz J, Cheng W, Brinker K. Label ranking by learning pairwise preferences. Artificial Intelligence. 2008;172:1897-1917.
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2008 | Journal Article | LibreCat-ID: 16167
Vanderlooy S, Hüllermeier E. A critical analysis of variants of the AUC. Machine Learning. 2008;72:247-272.
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2008 | Journal Article | LibreCat-ID: 16168
Fürnkranz J, Hüllermeier E, Mencia E, Brinker K. Multilabel classification via calibrated label ranking. Machine Learning. 2008;73(2):133-153.
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2008 | Journal Article | LibreCat-ID: 16169
Hüllermeier E, Brinker K. Learning valued preference structures for solving classification problems. Fuzzy Sets and Systems. 2008;159(18):2337-2352.
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2008 | Journal Article | LibreCat-ID: 16184
Beringer J, Hüllermeier E. Case-based learning in a bipolar possibilistic framework. International Journal of Intelligent Systems. 2008;23(10):1119-1134.
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2008 | Book Chapter | LibreCat-ID: 16225
Hüllermeier E. Granular computing in machine learning and data mining. In: Pedrycz W, Skowron A, Kreinovich V, eds. Handbook on Granular Computing. John Wiley and Sons; 2008:889-906.
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