center_scale: Function to scale and/or center the data

In ClusterR: Gaussian Mixture Models, K-Means, Mini-Batch-Kmeans, K-Medoids and Affinity Propagation Clustering

Function to scale and/or center the data

Description

Function to scale and/or center the data

Usage

center_scale(data, mean_center = TRUE, sd_scale = TRUE)

Arguments

data	matrix or data frame
mean_center	either TRUE or FALSE. If mean_center is TRUE then the mean of each column will be subtracted
sd_scale	either TRUE or FALSE. See the details section for more information

Details

If sd_scale is TRUE and mean_center is TRUE then each column will be divided by the standard deviation. If sd_scale is TRUE and mean_center is FALSE then each column will be divided by sqrt( sum(x^2) / (n-1) ). In case of missing values the function raises an error. In case that the standard deviation equals zero then the standard deviation will be replaced with 1.0, so that NaN's can be avoided by division

Value

a matrix

Examples

data(dietary_survey_IBS)

dat = dietary_survey_IBS[, -ncol(dietary_survey_IBS)]

dat = center_scale(dat, mean_center = TRUE, sd_scale = TRUE)

ClusterR documentation built on June 22, 2024, 10:28 a.m.