xenial (1) mlpack_hmm_train.1.gz

NAME

       mlpack_hmm_train - hidden markov model (hmm) training

SYNOPSIS

        mlpack_hmm_train [-h] [-v] -i string -t string [-b] [-g int] [-l string] [-m string] [-o string] [-s int] [-n int] [-T double] -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.

       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 OPTIONS

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

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

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 (optional). Default value ''.

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

       --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.

ADDITIONAL INFORMATION

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

                                                                                             mlpack_hmm_train(1)