To cluster, or not to cluster: An analysis of clusterability methods

PATTERN RECOGNITION

卷:88

Article

Adolfsson, Andreas¹  Ackerman, Margareta¹  Brownstein, Naomi C.² 

[1] Santa Clam Univ, Dept Comp Engn, 500 Camino Real, Santa Clara, CA 95053 USA

[2] Florida State Univ, Dept Behav Sci & Social Med, 1115 West Call St, Tallahassee, FL 32306 USA

关键词: Clusterability;    Cluster structure;    Cluster tendency;    Dimension reduction;    Multimodality tests;   

DOI  :  10.1016/j.patcog.2018.10.026

来源: Elsevier

【 摘 要 】

Clustering is an essential data mining tool that aims to discover inherent cluster structure in data. For most applications, applying clustering is only appropriate when cluster structure is present. As such, the study of clusterability, which evaluates whether data possesses such structure, is an integral part of cluster analysis. However, methods for evaluating clusterability vary radically, making it challenging to select a suitable measure. In this paper, we perform an extensive comparison of measures of clusterability and provide guidelines that clustering users can reference to select suitable measures for their applications. (C) 2018 Elsevier Ltd. All rights reserved.

【 授权许可】

Free