Lukas Pfannschmidt
lpfannschmidt@techfak.uni-bielefeld.de
PEVZ-ID
7 Publikationen
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2020 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2939517Pfannschmidt, L., et al., 2020. Feature Relevance Determination for Ordinal Regression in the Context of Feature Redundancies and Privileged Information. Neurocomputing.PUB | DOI | Download (ext.) | WoS | arXiv
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2019 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2933893Pfannschmidt, L., et al., 2019. Feature Relevance Bounds for Ordinal Regression. In M. Verleysen, ed. Proceedings of the 27th European Symposium on Artificial Neural Networks (ESANN 2019). Louvain-la-Neuve: i6doc.PUB | Download (ext.) | arXiv
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2019 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2935456Pfannschmidt, L., et al., 2019. FRI - Feature Relevance Intervals for Interpretable and Interactive Data Exploration. Presented at the 16th IEEE International Conference on Computational Intelligence in Bioinformatics and Computational Biology, Certosa di Pontignano, Siena - Tuscany, Italy.PUB | PDF | DOI | arXiv
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2017 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2908201Göpfert, C., Pfannschmidt, L., & Hammer, B., 2017. Feature Relevance Bounds for Linear Classification. In M. Verleysen, ed. Proceedings of the ESANN, 24th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. Louvain-la-Neuve: Ciaco - i6doc.com, pp. 187--192.PUB | Dateien verfügbar | Download (ext.)