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Improvement Study and Application Based on K-Means Clustering Algorithm

机译:基于K-Means聚类算法的改进研究与应用

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The k-means algorithm is the most classic cluster algorithm based on the distance in the Cluster-analysis. Because of the shortcomings of the traditional k-means algorithm, this paper proposes an improved k-means algorithm which is researched and analyzed. The results, putting into this improved algorithm to analyze the data of a shopping mall, prove that the algorithm can improve the quality of cluster algorithm and attain a rather good result.
机译:K-Means算法是基于群集分析中距离的最经典的集群算法。由于传统的K-Means算法的缺点,本文提出了一种改进的K-Means算法,其研究和分析。结果,进入这种改进的算法来分析购物中心的数据,证明该算法可以提高群集算法的质量并获得相当好的结果。

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