To Cluster, or Not to Cluster: How to Answer theestion
نویسندگان
چکیده
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 utilize to select suitable measures for their applications. ACM Reference format: Andreas Adolfsson, Margareta Ackerman*, and Naomi C. Brownstein*. 2016. To Cluster, or Not to Cluster: How to Answer the estion . In Proceedings of Knowledge Discovery from Data, Halifax, Nova Scotia, Canada, August 13–17 (TKDD‘17), 9 pages. DOI: 10.1145/nnnnnnn.nnnnnnn
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