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Authors: Mateus Espadoto 1 ; Francisco Rodrigues 1 and Alexandru Telea 2

Affiliations: 1 Institute of Mathematics and Statistics, University of São Paulo, Brazil, Johann Bernoulli Institute, University of Groningen and The Netherlands ; 2 Johann Bernoulli Institute, University of Groningen and The Netherlands

ISBN: 978-989-758-354-4

Keyword(s): Machine Learning, Dimensionality Reduction, Image-based Visualization.

Abstract: Visualizing decision boundaries of modern machine learning classifiers can notably help in classifier design, testing, and fine-tuning. Dense maps are a very recent method that overcomes the key sparsity-related limitation of scatterplots for this task. However, the trustworthiness of dense maps heavily depends on the underlying dimensionality-reduction (DR) techniques they use. We design and perform a detailed study aimed at finding the best DR techniques to use when creating trustworthy dense maps, by studying a large collection of 28 DR algorithms, 4 classifiers, and 2 datasets from a real-world challenging classification problem. Our results show how one can pick suitable DR algorithms to create dense maps that help understanding classifier behavior.

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Paper citation in several formats:
Espadoto, M.; Rodrigues, F. and Telea, A. (2019). Visual Analytics of Multidimensional Projections for Constructing Classifier Decision Boundary Maps.In Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: IVAPP, ISBN 978-989-758-354-4, pages 28-38. DOI: 10.5220/0007260800280038

@conference{ivapp19,
author={Mateus Espadoto. and Francisco Caio M. Rodrigues. and Alexandru C. Telea.},
title={Visual Analytics of Multidimensional Projections for Constructing Classifier Decision Boundary Maps},
booktitle={Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: IVAPP,},
year={2019},
pages={28-38},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007260800280038},
isbn={978-989-758-354-4},
}

TY - CONF

JO - Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: IVAPP,
TI - Visual Analytics of Multidimensional Projections for Constructing Classifier Decision Boundary Maps
SN - 978-989-758-354-4
AU - Espadoto, M.
AU - Rodrigues, F.
AU - Telea, A.
PY - 2019
SP - 28
EP - 38
DO - 10.5220/0007260800280038

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