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 |
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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
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.