The separation between clusters is defined by the minimum distances of a point in the cluster to a point in another cluster. The number of clusters are provided. If not, the hierarchical clustering method is used to obtain the clusters. The separation between the clusters for dataset X is calculated. Same is done for dataset PX. An euclidean distance is then calculated between these separation for X and PX.
sep_dist(X, PX, clustering = FALSE, nclust = 3, type = "separation")a data.frame with two or three columns, the first two columns providing the dataset
a data.frame with two or three columns, the first two columns providing the dataset
LOGICAL; if TRUE, the third column is used as the clustering variable, by default FALSE
the number of clusters to be obtained by hierarchical clustering, by default nclust = 3
character string to specify which measure to use for distance, see ?cluster.stats for details
distance between X and PX
if(require('fpc')) {
with(mtcars, sep_dist(data.frame(wt, mpg, as.numeric(as.factor(mtcars$cyl))),
data.frame(sample(wt), mpg, as.numeric(as.factor(mtcars$cyl))),
clustering = TRUE))
}
#> Loading required package: fpc
#> [1] 0.6016821
if (require('fpc')) {
with(mtcars, sep_dist(data.frame(wt, mpg, as.numeric(as.factor(mtcars$cyl))),
data.frame(sample(wt), mpg, as.numeric(as.factor(mtcars$cyl))),
nclust = 3))
}
#> [1] 0.7011197