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Journal of Visualization

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30-07-2020 | Regular Paper

SADIRE: a context-preserving sampling technique for dimensionality reduction visualizations

Authors: Wilson Estécio Marcilio-Jr, Danilo Medeiros Eler

Published in: Journal of Visualization | Issue 6/2020

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Abstract

Sampling techniques are widely used in the effort to reduce complexity and improve interpretability of datasets. Given the enormous availability of data, these techniques try to select representative data points that inherently reflect the data structure. In this work, we propose a novel sampling technique that preserves the structures imposed by dimensionality reduction techniques when visualized as scatter plots. In the experiments, we demonstrate how our technique is able to reflect the class boundaries and layout structures, besides decreasing redundancy of the datasets visualized as scatter plots. We also provide an user experiment regarding the perception of sampling from scatter plot visualizations.

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Title: SADIRE: a context-preserving sampling technique for dimensionality reduction visualizations
Authors: Wilson Estécio Marcilio-Jr
Danilo Medeiros Eler
Publication date: 30-07-2020
Publisher: Springer Berlin Heidelberg
Published in: Journal of Visualization / Issue 6/2020
Print ISSN: 1343-8875
Electronic ISSN: 1875-8975
DOI: https://doi.org/10.1007/s12650-020-00685-4

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