Résumé
Non-linear dimensionality reduction techniques offer insights into complex datasets, yet interpreting them poses challenges. While some papers provide methods for explaining DR, and others focus on interactively exploring embeddings, there are currently no works that seamlessly combine both aspects. Our contributions, Insight-SNE, propose an interactive tool that allows exploring t-SNE embeddings and their related gradient-based explanations, as well as its evaluation with expert users.
langue originale | Anglais |
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titre | European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning |
Sous-titre | ESANN |
Editeur | ESANN (i6doc.com) |
Etat de la publication | Publié - 2024 |