cash: CASH clustering algorithm
In lenaWitterauf/rElki: An R interface to Java package ELKI (Version 0.7.5)

Description Usage Arguments Value See Also Examples

cash returns a list of clusters for the given data_matrix, formed according to CASH.

1	cash(data_matrix, minpts, maxlevel, jitter, adjust = NA, mindim = NA)

`data_matrix`	numeric Matrix containing data the clusters are calculated for. Rows are treated as observations, columns as features.
`minpts`	Number. Threshold for minimum number of points in a cluster. Has to be >= 1.
`maxlevel`	Number. Maximum level for splitting the hypercube. Has to be >= 1.
`jitter`	Number. Maximum jitter for distance values. Has to be > 0.
`adjust`	Boolean. Apply adjustment heuristic for interval choosing.
`mindim`	Number. Minimum dimensionality of the subspaces to be found.

List of clusters. The indices of each cluster belong to the indices in the given original data_matrix

https://elki-project.github.io/releases/release0.7.5/javadoc/de/lmu/ifi/dbs/elki/algorithm/clustering/correlation/CASH.html for ELKI documentation.

data_matrix <- matrix(c(1:30), nrow=10, ncol=3)
result      <- cash(data_matrix, 5, 10, 1, adjust = TRUE)
for(cluster_index in c(1:length(result))) {
    print(paste('Cluster: ', cluster_index))
    print(paste('Indices: ', paste(result[[cluster_index]], collapse=',')))
}