R: GMM Sample Generator

gmm_generate {mlpack} | R Documentation

## GMM Sample Generator

### Description

A sample generator for pre-trained GMMs. Given a pre-trained GMM, this can sample new points randomly from that distribution.

### Usage

    gmm_generate(input_model, samples, seed = NA, verbose = FALSE)

### Arguments

`input_model` | Input GMM model to generate samples from (GMM).
`samples` | Number of samples to generate (integer).
`seed` | Random seed. If 0, 'std::time(NULL)' is used. Default value "0" (integer).
`verbose` | Display informational messages and the full list of parameters and timers at the end of execution. Default value "FALSE" (logical).

### Details

This program is able to generate samples from a pre-trained GMM (use gmm_train to train a GMM). The pre-trained GMM must be specified with the "input_model" parameter. The number of samples to generate is specified by the "samples" parameter. Output samples may be saved with the "output" output parameter.

### Value

A list with several components:

`output` | Matrix to save output samples in (numeric matrix).

### Author(s)

mlpack developers

### Examples

    # The following command can be used to generate 100 samples from the
    # pre-trained GMM "gmm" and store those generated samples in "samples":

    ## Not run:
    output <- gmm_generate(input_model=gmm, samples=100)
    samples <- output$output

    ## End(Not run)

[Package mlpack version 3.4.2.1 Index]