ConfusionFlow : A Model-Agnostic Visualization for Temporal Analysis of Classifier Confusion
Classifiers are among the most widely used supervised machine learning algorithms. Many classification models exist, and choosing the right one for a given task is difficult. During model selection and debugging, data scientists need to assess classifiers' performances, evaluate their learning...
Ausführliche Beschreibung
Bibliographische Detailangaben
| Veröffentlicht in: | IEEE transactions on visualization and computer graphics. - 1996. - 28(2022), 2 vom: 30. Feb., Seite 1222-1236
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| 1. Verfasser: |
Hinterreiter, Andreas
(VerfasserIn) |
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| Weitere Verfasser: |
Ruch, Peter,
Stitz, Holger,
Ennemoser, Martin,
Bernard, Jurgen,
Strobelt, Hendrik,
Streit, Marc |
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| Format: | Online-Aufsatz
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| Sprache: | English |
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| Veröffentlicht: |
2022
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| Zugriff auf das übergeordnete Werk: | IEEE transactions on visualization and computer graphics
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| Schlagworte: | Journal Article
Research Support, Non-U.S. Gov't |
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