Author(s)

Bin Yan, Guangming Deng

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

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.

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

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.