A new density-based sampling algorithm

DOI

10.2991/ifsa-eusflat-15.2015.24How to use a DOI?

Keywords

Density, distance, space coverage, clustering, Rand index.

Abstract

To face the big data challenge, sampling can be used as a preprocessing step for clustering. In this paper, an hybrid algorithm is proposed. It is density-based while managing distance concepts. The algorithm behavior is investigated using synthetic and realworld data sets. The first experiments proved it can be accurate, according to the Rand Index, with both k-means and hierarchical clustering algorithms.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Frédéric Ros
AU  - Serge Guillaume
PY  - 2015/06
DA  - 2015/06
TI  - A new density-based sampling algorithm
BT  - Proceedings of the 2015 Conference of the International Fuzzy Systems Association and the European Society for Fuzzy Logic and Technology
PB  - Atlantis Press
SP  - 145
EP  - 151
SN  - 1951-6851
UR  - https://doi.org/10.2991/ifsa-eusflat-15.2015.24
DO  - 10.2991/ifsa-eusflat-15.2015.24
ID  - Ros2015/06
ER  -