A Parameter Adaptive Clustering Algorithm Based on Reference Points and Density

DOI

10.2991/lemcs-15.2015.131How to use a DOI?

Keywords

Data mining; clustering; SA-CURD; CURD

Abstract

CURD is one type of clustering algorithm based on reference point and density. This algorithm is similar to DBSCAN in processing arbitrary shape clustering ability and has linear time complexity of K-MEANS algorithm. CURD algorithm needs to set Radius and t, so the whole process of clustering needs manual intervention which has the similarity with most of clustering algorithm. This paper proposes SA-CURD clustering algorithm based on CURD which can automatically set Radius and t by analyzing dataset statistics, in order avoid manual intervention in the process of clustering and achieve complete automation. Experiments show that SA-CURD can rationally choose Radius and t and get highly precise clustering results.

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  - Cheng Ouyang
AU  - Jun Tan
AU  - Jun Yu
AU  - ZhiFan Zeng
PY  - 2015/07
DA  - 2015/07
TI  - A Parameter Adaptive Clustering Algorithm Based on Reference Points and Density
BT  - Proceedings of the International Conference on Logistics, Engineering, Management and Computer Science
PB  - Atlantis Press
SP  - 672
EP  - 675
SN  - 1951-6851
UR  - https://doi.org/10.2991/lemcs-15.2015.131
DO  - 10.2991/lemcs-15.2015.131
ID  - Ouyang2015/07
ER  -