Improved K-means Algorithm Based on the Clustering Reliability Analysis

DOI

10.2991/isci-15.2015.326How to use a DOI?

Keywords

clustering analysis; k-means algorithm; reliability analysis

Abstract

Clustering analysis is the basic of data mining, and K-means algorithm is the simplest clustering algorithm. However, traditional K-means algorithm has many defects-instable K value determinations, non-universal applicable SSE etc. Consequently, we introduced an improved K-means algorithm basing on the clustering reliability analysis. The algorithm effectively solves the problem on uneven density and large differences in the amount of data clustering.

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  - Hong Zhang
AU  - Hong Yu
AU  - Ying Li
AU  - Baofang Hu
PY  - 2015/01
DA  - 2015/01
TI  - Improved K-means Algorithm Based on the Clustering Reliability Analysis
BT  - Proceedings of the 2015 International Symposium on Computers & Informatics
PB  - Atlantis Press
SP  - 2516
EP  - 2523
SN  - 2352-538X
UR  - https://doi.org/10.2991/isci-15.2015.326
DO  - 10.2991/isci-15.2015.326
ID  - Zhang2015/01
ER  -