Research Article
Improving the Cluster Efficiency on Sea Level Rise Dataset using Data Discretization
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
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| Volume 102 - Issue 13 |
| Published: September 2014 |
| Authors: Sharon Dominick, T. Abdul Razak |
10.5120/17875-8856
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Sharon Dominick, T. Abdul Razak . Improving the Cluster Efficiency on Sea Level Rise Dataset using Data Discretization. International Journal of Computer Applications. 102, 13 (September 2014), 15-18. DOI=10.5120/17875-8856
@article{ 10.5120/17875-8856,
author = { Sharon Dominick,T. Abdul Razak },
title = { Improving the Cluster Efficiency on Sea Level Rise Dataset using Data Discretization },
journal = { International Journal of Computer Applications },
year = { 2014 },
volume = { 102 },
number = { 13 },
pages = { 15-18 },
doi = { 10.5120/17875-8856 },
publisher = { Foundation of Computer Science (FCS), NY, USA }
}
%0 Journal Article
%D 2014
%A Sharon Dominick
%A T. Abdul Razak
%T Improving the Cluster Efficiency on Sea Level Rise Dataset using Data Discretization%T
%J International Journal of Computer Applications
%V 102
%N 13
%P 15-18
%R 10.5120/17875-8856
%I Foundation of Computer Science (FCS), NY, USA
Abstract
Rising sea levels, an effect of global warming, is a cause of concern and it is likely to affect the developing countries. With respect to the data set published for research at the World Bank, clustering a data mining technique is applied to detect the most likely to be affected regions. When tested with the k-Means clustering technique, the result of the clustering process reveals a lot of imperfections; this research analyzes the use of data discretization to improve the quality of the clustering process.
References
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