RfX: A Design Study for the Interactive Exploration of a Random Forest to Enhance Testing Procedures for Electrical Engines

dc.contributor.authorEirich, J.en_US
dc.contributor.authorMünch, M.en_US
dc.contributor.authorJäckle, D.en_US
dc.contributor.authorSedlmair, M.en_US
dc.contributor.authorBonart, J.en_US
dc.contributor.authorSchreck, T.en_US
dc.contributor.editorHauser, Helwig and Alliez, Pierreen_US
dc.date.accessioned2022-10-11T05:24:57Z
dc.date.available2022-10-11T05:24:57Z
dc.date.issued2022
dc.description.abstractRandom Forests (RFs) are a machine learning (ML) technique widely used across industries. The interpretation of a given RF usually relies on the analysis of statistical values and is often only possible for data analytics experts. To make RFs accessible to experts with no data analytics background, we present RfX, a Visual Analytics (VA) system for the analysis of a RF's decision‐making process. RfX allows to interactively analyse the properties of a forest and to explore and compare multiple trees in a RF. Thus, its users can identify relationships within a RF's feature subspace and detect hidden patterns in the model's underlying data. We contribute a design study in collaboration with an automotive company. A formative evaluation of RFX was carried out with two domain experts and a summative evaluation in the form of a field study with five domain experts. In this context, new hidden patterns such as increased eccentricities in an engine's rotor by observing secondary excitations of its bearings were detected using analyses made with RfX. Rules derived from analyses with the system led to a change in the company's testing procedures for electrical engines, which resulted in 80% reduced testing time for over 30% of all components.en_US
dc.description.number6
dc.description.sectionheadersMajor Revision from EuroVis Symposium
dc.description.seriesinformationComputer Graphics Forum
dc.description.volume41
dc.identifier.doi10.1111/cgf.14452
dc.identifier.issn1467-8659
dc.identifier.pages302-315
dc.identifier.urihttps://doi.org/10.1111/cgf.14452
dc.identifier.urihttps://diglib.eg.org:443/handle/10.1111/cgf14452
dc.publisher© 2022 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd.en_US
dc.subjecthuman–computer interfaces
dc.subjectinteraction
dc.subjectvisual analytics
dc.subjectvisualization
dc.titleRfX: A Design Study for the Interactive Exploration of a Random Forest to Enhance Testing Procedures for Electrical Enginesen_US
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