FRI - Feature Relevance Intervals for Interpretable and Interactive Data Exploration
Pfannschmidt L, Göpfert C, Neumann U, Heider D, Hammer B (2019)
Presented at the 16th IEEE International Conference on Computational Intelligence in Bioinformatics and Computational Biology, Certosa di Pontignano, Siena - Tuscany, Italy.
Konferenzbeitrag
| Veröffentlicht | Englisch
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FRI_CIBCB_2019_preprint.pdf
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Autor*in
Pfannschmidt, LukasUniBi 
;
Göpfert, ChristinaUniBi ;
Neumann, Ursula;
Heider, Dominik;
Hammer, BarbaraUniBi
;
Göpfert, ChristinaUniBi ;
Neumann, Ursula;
Heider, Dominik;
Hammer, BarbaraUniBi Einrichtung
Abstract / Bemerkung
Most existing feature selection methods are insufficient for analytic
purposes as soon as high dimensional data or redundant sensor signals are dealt
with since features can be selected due to spurious effects or correlations
rather than causal effects. To support the finding of causal features in
biomedical experiments, we hereby present FRI, an open source Python library
that can be used to identify all-relevant variables in linear classification
and (ordinal) regression problems. Using the recently proposed feature
relevance method, FRI is able to provide the base for further general
experimentation or in specific can facilitate the search for alternative
biomarkers. It can be used in an interactive context, by providing model
manipulation and visualization methods, or in a batch process as a filter
method.
Stichworte
global feature relevance;
feature selection;
interpretability;
interactive biomarker discovery
Erscheinungsjahr
2019
Urheberrecht / Lizenzen
Konferenz
16th IEEE International Conference on Computational Intelligence in Bioinformatics and Computational Biology
Konferenzort
Certosa di Pontignano, Siena - Tuscany, Italy
Konferenzdatum
2019-07-09 – 2019-07-11
eISBN
978-1-7281-1462-0
Page URI
https://pub.uni-bielefeld.de/record/2935456
Zitieren
Pfannschmidt L, Göpfert C, Neumann U, Heider D, Hammer B. 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.
Pfannschmidt, L., Göpfert, C., Neumann, U., Heider, D., & Hammer, B. (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. doi:10.1109/CIBCB.2019.8791489
Pfannschmidt, Lukas, Göpfert, Christina, Neumann, Ursula, Heider, Dominik, and Hammer, Barbara. 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 .
Pfannschmidt, L., Göpfert, C., Neumann, U., Heider, D., and Hammer, B. (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.
Pfannschmidt, 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.
L. Pfannschmidt, et al., “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, 2019.
Pfannschmidt, L., Göpfert, C., Neumann, U., Heider, D., Hammer, B.: 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 (2019).
Pfannschmidt, Lukas, Göpfert, Christina, Neumann, Ursula, Heider, Dominik, and Hammer, Barbara. “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, 2019.
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