# predict_GMM: Prediction function for a Gaussian Mixture Model object

## Description

Prediction function for a Gaussian Mixture Model object

## Usage

predict_GMM(data, CENTROIDS, COVARIANCE, WEIGHTS)

## Arguments

CENTROIDS

matrix or data frame containing the centroids (means), stored as row vectors

COVARIANCE

matrix or data frame containing the diagonal covariance matrices, stored as row vectors

WEIGHTS

vector containing the weights

## Value

a list consisting of the log-likelihoods, cluster probabilities and cluster labels.

## Details

This function takes the centroids, covariance matrix and weights from a trained model and returns the log-likelihoods, cluster probabilities and cluster labels for new data.

## Examples

# NOT RUN {
data(dietary_survey_IBS)
dat = as.matrix(dietary_survey_IBS[, -ncol(dietary_survey_IBS)])
dat = center_scale(dat)
gmm = GMM(dat, 2, "maha_dist", "random_subset", 10, 10)
# pr = predict_GMM(dat, gmm$centroids, gmm$covariance_matrices, gmm$weights)
# }