Summarize a G-means Clustering Object

Summarize the result of a G-means clustering: the number of clusters found, the settings used to fit the model, a per-cluster table of sizes, within-cluster sums of squares and centers, and the overall sums of squares.

Usage

# S3 method for class 'gmeans'
summary(object, ...)

# S3 method for class 'summary.gmeans'
print(x, digits = max(3L, getOption("digits") - 3L), ...)

Arguments

object

(gmeans())
An object of class "gmeans".

...

(any)
Additional arguments. Currently unused.

x

(summary.gmeans())
An object of class "summary.gmeans".

digits

(integer(1))
Number of significant digits to print.

Value

summary() returns an object of class "summary.gmeans", a list with components:

• k, k_init, k_max, level: the number of clusters found and the settings used to fit the model.

• clusters: a data.frame() with one row per cluster and the columns cluster, size, withinss, followed by the cluster centers.

• totss, tot.withinss, betweenss, iter: as in stats::kmeans().

print() returns x invisibly.

See also

gmeans()

Examples

x <- as.matrix(iris[, -5])
cl <- gmeans(x)
summary(cl)
#> G-means clustering with 2 clusters (k_init = 1, k_max = 10, level = 0.0001)
#> 
#>  cluster size withinss Sepal.Length Sepal.Width Petal.Length Petal.Width
#>        1   97   123.80        6.301       2.887        4.959      1.6959
#>        2   53    28.55        5.006       3.370        1.560      0.2906
#> 
#> Total SS: 681.4, within SS: 152.3, between SS: 529 (77.64% of total)