期刊文献+

Improved Clustering Algorithm Based on Density-Isoline

Improved Clustering Algorithm Based on Density-Isoline
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摘要 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. 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.
机构地区 College of Science
出处 《Open Journal of Statistics》 2015年第4期303-310,共8页 统计学期刊(英文)
关键词 Density-Isolines Density-Based CLUSTERING CLUSTERING ALGORITHM Noise Density-Isolines Density-Based Clustering Clustering Algorithm Noise
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