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)
## S3 method for class 'GMMCluster'
predict(object, newdata, ...)
```

### 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 |

`object` , `newdata` , `...` |
arguments for the 'predict' generic |

### 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 1.3.3 Index]