Fundamental clustering algorithms suite
Michael C. Thrun, Quirin Stier
Abstract
The article presents immediate access to over fifty fundamental clustering algorithms. Additionally, access to clustering benchmark datasets published priorly as “Fundamental Clustering Problems Suite” (FCPS) is provided. The software library is named “FCPS”, available in R on CRAN and accessible within Python. The input and output of clustering algorithms are standardized to enable users a swift execution of cluster analysis. By combining mirrored-density plots (MD plots) with statistical testing, FCPS provides a tool to investigate the cluster-tendency quickly before the cluster analysis itself. Common clustering challenges can be generated with an arbitrary sample size. Additionally, FCPS sums up 26 indicators intending to estimate the number of clusters and provides an appropriate implementation of the clustering accuracy for more than two clusters.