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...
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Détails bibliographiques
| Publié dans: | IEEE transactions on visualization and computer graphics. - 1996. - 28(2022), 2 vom: 30. Feb., Seite 1222-1236
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| Auteur principal: |
Hinterreiter, Andreas
(Auteur) |
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| Autres auteurs: |
Ruch, Peter,
Stitz, Holger,
Ennemoser, Martin,
Bernard, Jurgen,
Strobelt, Hendrik,
Streit, Marc |
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| Format: | Article en ligne
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| Langue: | English |
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| Publié: |
2022
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| Accès à la collection: | IEEE transactions on visualization and computer graphics
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| Sujets: | Journal Article
Research Support, Non-U.S. Gov't |
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