kmeans_cluster: k-means clustering

In UBC-MDS/kmeans_R: R package aimed towards a user-friendly way of exploring and implementing k-means clustering.

Description

k-means clustering

Usage

kmeans_cluster(data, centers, max_iter = 100)

Arguments

data	- The data object (data frame or matrix) that k-means clustering will be applied to.
centers	- The matrix containing the initial centers as computed by kmeans_init.

Value

- The data object (as a data frame) with a column containing cluster assignments.

Examples

x <- runif(100, min = 0, max = 10) + rep(c(0, 10), 50)
y <- rnorm(100, 5, 1) + rep(c(0, 10), 50)
data = data.frame(x = x, y = y)

centers <- kmeans_init(data = data, K = 2)
kmeans_cluster(data=data, centers=centers)

UBC-MDS/kmeans_R documentation built on May 22, 2019, 2:26 p.m.