gmm_generate | R Documentation |
A sample generator for pre-trained GMMs. Given a pre-trained GMM, this can sample new points randomly from that distribution.
gmm_generate(
input_model,
samples,
seed = NA,
verbose = getOption("mlpack.verbose", FALSE)
)
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 "getOption("mlpack.verbose", FALSE)" (logical). |
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.
A list with several components:
output |
Matrix to save output samples in (numeric matrix). |
mlpack developers
# 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)
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