A Dashboard for Simplifying Machine Learning Models using Feature Importances and Spurious Correlation Analysis

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dc.contributor.authorCech, Timen_US
dc.contributor.authorKohlros, Eriken_US
dc.contributor.authorScheibel, Willyen_US
dc.contributor.authorDöllner, Jürgenen_US
dc.contributor.editorKucher, Kostiantynen_US
dc.contributor.editorDiehl, Alexandraen_US
dc.contributor.editorGillmann, Christinaen_US
dc.date.accessioned2024-05-21T08:44:47Z
dc.date.available2024-05-21T08:44:47Z
dc.date.issued2024
dc.description.abstractMachine Learning models underlie a trade-off between accurracy and explainability. Given a trained, complex model, we contribute a dashboard that supports the process to derive more explainable models, here: Fast-and-Frugal Trees, with further introspection using feature importances and spurious correlation analyses. The dashboard further allows to iterate over the feature selection and assess the trees' performance in comparison to the complex model.en_US
dc.description.sectionheadersPosters
dc.description.seriesinformationEuroVis 2024 - Posters
dc.identifier.doi10.2312/evp.20241075
dc.identifier.isbn978-3-03868-258-5
dc.identifier.pages3 pages
dc.identifier.urihttps://doi.org/10.2312/evp.20241075
dc.identifier.urihttps://diglib.eg.org/handle/10.2312/evp20241075
dc.publisherThe Eurographics Associationen_US
dc.rightsAttribution 4.0 International License
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectCCS Concepts: Human-centered computing → Visualization techniques; Information systems → Users and interactive retrieval
dc.subjectHuman centered computing → Visualization techniques
dc.subjectInformation systems → Users and interactive retrieval
dc.titleA Dashboard for Simplifying Machine Learning Models using Feature Importances and Spurious Correlation Analysisen_US
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