ClusterR (version 1.2.2)

predict_KMeans: Prediction function for the k-means

Description

Prediction function for the k-means

Usage

predict_KMeans(data, CENTROIDS, threads = 1)

Arguments

data

matrix or data frame

CENTROIDS

a matrix of initial cluster centroids. The rows of the CENTROIDS matrix should be equal to the number of clusters and the columns should be equal to the columns of the data.

threads

an integer specifying the number of cores to run in parallel

Value

a vector (clusters)

Details

This function takes the data and the output centroids and returns the clusters.

Examples

# NOT RUN {
data(dietary_survey_IBS)

dat = dietary_survey_IBS[, -ncol(dietary_survey_IBS)]

dat = center_scale(dat)

km = KMeans_rcpp(dat, clusters = 2, num_init = 5, max_iters = 100, initializer = 'kmeans++')

pr = predict_KMeans(dat, km$centroids, threads = 1)
# }