Research on Optimized Clustering Analysis Algorithm

Abstract:

In this paper an improved clustering analysis algorithm is proposed on the basis of randomly selected data in the CURE algorithm and the cluster centers setting in the K-NN algorithm. The combination of the two algorithms conquers the poor clustering accuracy in the CURE algorithm and the clustering deficiency on large data set in the K-NN algorithm. This paper first introduces the concept of clustering analysis and its real-life applications, then proceeds to describe the method of clustering analysis, and then introduces optimized CURE_KNN algorithm described in pseudo-code, at last the advantages of the algorithm are summarized.

• Periodical: Advanced Materials Research (Volume 811)
• Pages: 407-412
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.811.407
• Online since: September 2013
• Authors: Lin Tong, Di Wu
• Keywords: Algorithm (GA), Clustering Analysis, Efficiency

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