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For each cluster, computes the mean (or other indices) of the variables. Can be used to retrieve the centers of clusters. Also returns the within Sum of Squares.

Usage

cluster_centers(data, clusters, fun = mean, ...)

Arguments

data

A data.frame.

clusters

A vector with clusters assignments (must be same length as rows in data).

fun

What function to use, mean by default.

...

Other arguments to be passed to or from other functions.

Value

A dataframe containing the cluster centers. Attributes include performance statistics and distance between each observation and its respective cluster centre.

Examples

k <- kmeans(iris[1:4], 3)
cluster_centers(iris[1:4], clusters = k$cluster) #> Cluster n_Obs Sum_Squares Sepal.Length Sepal.Width Petal.Length Petal.Width #> 1 1 62 39.82097 5.901613 2.748387 4.393548 1.433871 #> 2 2 38 23.87947 6.850000 3.073684 5.742105 2.071053 #> 3 3 50 15.15100 5.006000 3.428000 1.462000 0.246000 cluster_centers(iris[1:4], clusters = k$cluster, fun = median)
#>   Cluster n_Obs Sum_Squares Sepal.Length Sepal.Width Petal.Length Petal.Width
#> 1       1    62    39.82097          5.9         2.8         4.50         1.4
#> 2       2    38    23.87947          6.7         3.0         5.65         2.1
#> 3       3    50    15.15100          5.0         3.4         1.50         0.2