@inproceedings{085316ac55654c92b1d77c3b5d41621c,
title = "VisCoDeR: A tool for visually comparing dimensionality reduction algorithms",
abstract = "We propose VisCoDeR, a tool that leverages comparative visualization to support learning and analyzing different dimensionality reduction (DR) methods. VisCoDeR fosters two modes. The Discover mode allows qualitatively comparing several DR results by juxtaposing and linking the resulting scatterplots. The Explore mode allows for analyzing hundreds of differently parameterized DR results in a quantitative way. We present use cases that show that our approach helps to understand similarities and differences between DR algorithms.",
author = "Rene Cutura and Stefan Holzer and Micha{\"e}l Aupetit and Michael Sedlmair",
note = "Publisher Copyright: {\textcopyright} ESANN 2018 - Proceedings, European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning.; 26th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ESANN 2018 ; Conference date: 25-04-2018 Through 27-04-2018",
year = "2018",
language = "English",
series = "ESANN 2018 - Proceedings, European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning",
publisher = "i6doc.com publication",
pages = "105--110",
booktitle = "ESANN 2018 - Proceedings, European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning",
}