Research on K-Value Selection Method of K-Means Clustering Algorithm

Chunhui Yuan and Haitao Yang
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Chunhui Yuan: Graduate institute, Space Engineering University, Beijing 101400, China
Haitao Yang: Graduate institute, Space Engineering University, Beijing 101400, China

J, 2019, vol. 2, issue 2, 1-10

Abstract: Among many clustering algorithms, the K-means clustering algorithm is widely used because of its simple algorithm and fast convergence. However, the K-value of clustering needs to be given in advance and the choice of K-value directly affect the convergence result. To solve this problem, we mainly analyze four K-value selection algorithms, namely Elbow Method, Gap Statistic, Silhouette Coefficient, and Canopy; give the pseudo code of the algorithm; and use the standard data set Iris for experimental verification. Finally, the verification results are evaluated, the advantages and disadvantages of the above four algorithms in a K-value selection are given, and the clustering range of the data set is pointed out.

Keywords: Clustering; K-means; K-value; Convergence (search for similar items in EconPapers)
JEL-codes: I1 I10 I12 I13 I14 I18 I19 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (21)

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