Multi-Label Classification

Multi-label classification targets the prediction of multiple interdependent and non-exclusive binary target variables. Transformation-based algorithms transform the data set such that regular single-label algorithms can be applied to the problem. A special type of transformation-based classifiers are label compression methods, that compress the labels and then mostly use single label classifiers to predict the compressed labels.


Latino, Diogo; Wicker, Jörg; Gütlein, Martin; Schmid, Emanuel; Kramer, Stefan; Fenner, Kathrin

Eawag-Soil in enviPath: a new resource for exploring regulatory pesticide soil biodegradation pathways and half-life data Journal Article

Environmental Science: Process & Impact, 2017.

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Wicker, Jörg; Fenner, Kathrin; Kramer, Stefan

A Hybrid Machine Learning and Knowledge Based Approach to Limit Combinatorial Explosion in Biodegradation Prediction Incollection

Lässig, Jörg; Kersting, Kristian; Morik, Katharina (Ed.): Computational Sustainability, pp. 75-97, Springer International Publishing, Cham, 2016, ISBN: 978-3-319-31858-5.

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Wicker, Jörg; Tyukin, Andrey; Kramer, Stefan

A Nonlinear Label Compression and Transformation Method for Multi-Label Classification using Autoencoders Inproceedings

Bailey, James; Khan, Latifur; Washio, Takashi; Dobbie, Gill; Huang, Zhexue Joshua; Wang, Ruili (Ed.): The 20th Pacific Asia Conference on Knowledge Discovery and Data Mining (PAKDD), pp. 328-340, Springer International Publishing, Switzerland, 2016, ISBN: 978-3-319-31753-3.

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Wicker, Jörg; Lorsbach, Tim; Gütlein, Martin; Schmid, Emanuel; Latino, Diogo; Kramer, Stefan; Fenner, Kathrin

enviPath - The Environmental Contaminant Biotransformation Pathway Resource Journal Article

Nucleic Acid Research, 44 (D1), pp. D502-D508, 2016.

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Wicker, Jörg

Large Classifier Systems in Bio- and Cheminformatics PhD Thesis

Technische Universität München, 2013.

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Wicker, Jörg; Pfahringer, Bernhard; Kramer, Stefan

Multi-label Classification Using Boolean Matrix Decomposition Inproceedings

Proceedings of the 27th Annual ACM Symposium on Applied Computing, pp. 179–186, ACM, 2012, ISBN: 978-1-4503-0857-1.

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