279 citations · 286 across the 2 of their papers we have counts for
2 papers
stat.ML2018★ 279 cited
To Cluster, or Not to Cluster: An Analysis of Clusterability Methods
A. Adolfsson, M. Ackerman, N. C. Brownstein
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 st…
cs.LG2016★ 7 cited
An Effective and Efficient Approach for Clusterability Evaluation
Margareta Ackerman, Andreas Adolfsson, Naomi Brownstein
Clustering is an essential data mining tool that aims to discover inherent cluster structure in data. As such, the study of clusterability, which evaluates whether data possesses s…