tidy.kmeans {broom}

Tidy a(n) kmeans object

Description

Tidy summarizes information about the components of a model. A model component might be a single term in a regression, a single hypothesis, a cluster, or a class. Exactly what tidy considers to be a model component varies across models but is usually self-evident. If a model has several distinct types of components, you will need to specify which components to return.

Usage

## S3 method for class 'kmeans'
tidy(x, col.names = colnames(x$centers), ...)

Arguments

x

A kmeans object created by stats::kmeans().

col.names

Dimension names. Defaults to the names of the variables in x. Set to NULL to get names ⁠x1, x2, ...⁠.

...

Additional arguments. Not used. Needed to match generic signature only. Cautionary note: Misspelled arguments will be absorbed in ..., where they will be ignored. If the misspelled argument has a default value, the default value will be used. For example, if you pass conf.lvel = 0.9, all computation will proceed using conf.level = 0.95. Two exceptions here are:

• tidy() methods will warn when supplied an exponentiate argument if it will be ignored.

• augment() methods will warn when supplied a newdata argument if it will be ignored.

Value

A tibble::tibble() with columns:

cluster

A factor describing the cluster from 1:k.

size

Number of points assigned to cluster.

withinss

The within-cluster sum of squares.

See Also

tidy(), stats::kmeans()

Other kmeans tidiers: augment.kmeans(), glance.kmeans()

Examples

library(cluster)
library(modeldata)
library(dplyr)

data(hpc_data)

x <- hpc_data[, 2:5]

fit <- pam(x, k = 4)

tidy(fit)
glance(fit)
augment(fit, x)