predict_GMM: Prediction function for a Gaussian Mixture Model object

Description Usage Arguments Details Value Author(s) Examples

View source: R/clustering_functions.R

Description

Prediction function for a Gaussian Mixture Model object

Usage

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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

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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)

ClusterR documentation built on May 21, 2021, 9:07 a.m.