bionic (1) mlpack_hmm_train.1.gz

NAME

       mlpack_hmm_train - hidden markov model (hmm) training

SYNOPSIS

        mlpack_hmm_train [-h] [-v]

DESCRIPTION

       This  program  allows  a Hidden Markov Model to be trained on labeled or unlabeled data. It support three
       types of HMMs: discrete HMMs, Gaussian HMMs, or GMM HMMs.

       Either one input sequence can be specified (with --input_file), or, a  file  containing  files  in  which
       input  sequences  can be found (when --input_file and --batch are used together). In addition, labels can
       be provided in the file  specified  by  --labels_file,  and  if  --batch  is  used,  the  file  given  to
       --labels_file  should  contain a list of files of labels corresponding to the sequences in the file given
       to --input_file.

       The HMM is trained with the Baum-Welch algorithm if no labels are provided.  The tolerance of  the  Baum-
       Welch  algorithm  can  be  set with the --tolerance option. By default, the transition matrix is randomly
       initialized and the emission distributions are initialized to fit the extent of the data.

       Optionally, a pre-created HMM model can be used as  a  guess  for  the  transition  matrix  and  emission
       probabilities; this is specifiable with --model_file.

REQUIRED INPUT OPTIONS

       --input_file (-i) [string]
              File containing input observations.

       --type (-t) [string]
              Type of HMM: discrete | gaussian | gmm.

OPTIONAL INPUT OPTIONS

       --batch (-b)
              If true, input_file (and if passed, labels_file) are expected to contain a list of files to use as
              input observation sequences (and label sequences).

       --gaussians (-g) [int]
              Number of gaussians in each GMM (necessary when type is 'gmm'). Default value 0.

       --help (-h)
              Default help info.

       --info [string]
              Get help on a specific module or option.  Default value ''.

       --labels_file (-l) [string]
              Optional file of hidden states, used for labeled training. Default value ''.

       --model_file (-m) [string]
              Pre-existing HMM model file. Default value ''.

       --seed (-s) [int]
              Random seed. If 0, 'std::time(NULL)' is used.  Default value 0.

       --states (-n) [int]
              Number of hidden states in HMM (necessary, unless model_file is specified). Default value

              0.

       --tolerance (-T) [double]
              Tolerance of the Baum-Welch algorithm. Default value 1e-05.

       --verbose (-v)
              Display informational messages and the full list of parameters and timers at the end of execution.

       --version (-V)
              Display the version of mlpack.

OPTIONAL OUTPUT OPTIONS

       --output_model_file (-o) [string] File to save trained HMM to. Default value ''.

ADDITIONAL INFORMATION

ADDITIONAL INFORMATION

       For further information, including relevant papers,  citations,  and  theory,  For  further  information,
       including    relevant   papers,   citations,   and   theory,   consult   the   documentation   found   at
       http://www.mlpack.org or included with your consult the documentation found at  http://www.mlpack.org  or
       included with your DISTRIBUTION OF MLPACK.  DISTRIBUTION OF MLPACK.

                                                                              mlpack_hmm_train(16 November 2017)