Visual Analytics of Multidimensional Projections for Constructing Classifier Decision Boundary Maps

Mateus Espadoto, Francisco Caio M. Rodrigues, Alexandru C. Telea

2019

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.

Paper Citation

in Harvard Style

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 (VISIGRAPP 2019) - Volume 3: IVAPP; ISBN 978-989-758-354-4, SciTePress, pages 28-38. DOI: 10.5220/0007260800280038

in Bibtex Style

@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 (VISIGRAPP 2019) - Volume 3: IVAPP},
year={2019},
pages={28-38},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007260800280038},
isbn={978-989-758-354-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2019) - 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
PB - SciTePress