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]