Improved Clustering Algorithm Based on Density-Isoline

Bin Yan; Guangming Deng

doi:10.4236/ojs.2015.54032

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OJS> Vol.5 No.4, June 2015

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Improved Clustering Algorithm Based on Density-Isoline

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DOI: 10.4236/ojs.2015.54032 2,415 Downloads 2,846 Views

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Bin Yan, Guangming Deng

Affiliation(s)

College of Science, Guilin University of Technology, Guilin, China.

ABSTRACT

An improved clustering algorithm was presented based on density-isoline clustering algorithm. The new algorithm can do a better job than density-isoline clustering when dealing with noise, not having to literately calculate the cluster centers for the samples batching into clusters instead of one by one. After repeated experiments, the results demonstrate that the improved density-isoline clustering algorithm is significantly more efficiency in clustering with noises and overcomes the drawbacks that traditional algorithm DILC deals with noise and that the efficiency of running time is improved greatly.

KEYWORDS

Density-Isolines, Density-Based Clustering, Clustering Algorithm, Noise

Conflicts of Interest

The authors declare no conflicts of interest.

Cite this paper

Yan, B. and Deng, G. (2015) Improved Clustering Algorithm Based on Density-Isoline. Open Journal of Statistics, 5, 303-310. doi: 10.4236/ojs.2015.54032.

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