R: Prediction function for a Gaussian Mixture Model object

predict_GMM {ClusterR}

R Documentation

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

`data`	matrix or data frame
`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

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.

Value

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

Author(s)

Lampros Mouselimis

Examples


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)

[Package ClusterR version 1.2.2 Index]