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ORCIDUrsula Neumann
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2010 – 2019
- 2019
[j4]Giuliano Armano, Alessandro Giuliani
, Ursula Neumann, Nikolas Rothe, Dominik Heider:
Phi-Delta-Diagrams: Software Implementation of a Visual Tool for Assessing Classifier and Feature Performance. Mach. Learn. Knowl. Extr. 1(1): 121-137 (2019)- [c2]Lukas Pfannschmidt, Christina Göpfert, Ursula Neumann, Dominik Heider, Barbara Hammer:
FRI-Feature Relevance Intervals for Interpretable and Interactive Data Exploration. CIBCB 2019: 1-10 - [i1]Lukas Pfannschmidt, Christina Göpfert, Ursula Neumann, Dominik Heider, Barbara Hammer:
FRI - Feature Relevance Intervals for Interpretable and Interactive Data Exploration. CoRR abs/1903.00719 (2019) - 2018
- [b1]Ursula Neumann:
Stability and Accuracy Analysis of a Feature Selection Ensemble for Binary Classification in Biomedical Datasets. Technical University Munich, Germany, 2018 - 2017
- [j3]Ursula Neumann, Nikita Genze, Dominik Heider:
EFS: an ensemble feature selection tool implemented as R-package and web-application. BioData Min. 10(1): 21:1-21:9 (2017) - 2016
- [j2]Mona Riemenschneider, Robin Senge, Ursula Neumann, Eyke Hüllermeier, Dominik Heider:
Exploiting HIV-1 protease and reverse transcriptase cross-resistance information for improved drug resistance prediction by means of multi-label classification. BioData Min. 9: 10 (2016) - [j1]Ursula Neumann, Mona Riemenschneider, Jan-Peter Sowa, Theodor Baars, Julia Kälsch, Ali Canbay, Dominik Heider:
Compensation of feature selection biases accompanied with improved predictive performance for binary classification by using a novel ensemble feature selection approach. BioData Min. 9: 36:1-36:14 (2016) - [c1]Ursula Neumann, Dominik Heider:
The EFS-Server: A Web-Application for Feature Selection in Binary Classification. KDWeb 2016
Coauthor Index
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