Research on K-means clustering algorithm and its implementation

DOI

10.2991/iccsee.2013.452How to use a DOI?

Keywords

K-means, Clustering center, Data mining, algorithm.

Abstract

K-means algorithm is a kind of clustering analysis based on partition algorithm, it through constant iteration to clustering, when algorithm converges to an end conditions, and the output iterative process termination clustering results. Because its algorithm is simple, and easy to realize thoughts of large-scale data clustering, so k-means algorithm has become one of the most commonly used one of the clustering algorithm. K-means algorithm can find about clustering error local optimal solution, be applied in many clustering on the question of the rapid iteration algorithm. In this paper, we deeply research and analysis of the K-means clustering algorithm in the cluster analysis and analysis of its advantages and disadvantage, finally, we implement the K-means and do an experiment for application.

Copyright

© 2013, 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  - Jianming Cui
AU  - Jianming Liu
AU  - Zhouyu Liao
PY  - 2013/03
DA  - 2013/03
TI  - Research on K-means clustering algorithm and its implementation
BT  - Proceedings of the 2nd International Conference on Computer Science and Electronics Engineering (ICCSEE 2013)
PB  - Atlantis Press
SP  - 1804
EP  - 1806
SN  - 1951-6851
UR  - https://doi.org/10.2991/iccsee.2013.452
DO  - 10.2991/iccsee.2013.452
ID  - Cui2013/03
ER  -