R: Prediction function for the k-means

predict_KMeans {ClusterR} | R Documentation

## 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

### Details

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

### Value

a vector (clusters)

### Author(s)

Lampros Mouselimis

### Examples

    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)

[Package ClusterR version 1.2.2 Index]