NAME

       mlpack_hmm_train - hidden markov model (hmm) training

SYNOPSIS

        mlpack_hmm_train -i string [-b bool] [-g int] [-m unknown] [-l string] [-s int] [-n int] [-T double] [-t string] [-V bool] [-M unknown] [-h -v]

DESCRIPTION

       This  program  allows a Hidden Markov Model to be trained on labeled or unlabeled data. It
       supports four types of HMMs: Discrete HMMs, Gaussian HMMs, GMM HMMs, or Diagonal GMM HMMs

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

       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 (-T)'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 ’--output_model_file (-M)'.

REQUIRED INPUT OPTIONS

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

OPTIONAL INPUT OPTIONS

       --batch (-b) [bool]
              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) [bool]
              Default help info.

       --info [string]
              Print help on a specific option. Default value ''.

       --input_model_file (-m) [unknown]
              Pre-existing HMM model to initialize training with.

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

       --type (-t) [string]
              Type of HMM: discrete | gaussian | diag_gmm | gmm. Default value 'gaussian'.

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

       --version (-V) [bool]
              Display the version of mlpack.

OPTIONAL OUTPUT OPTIONS

       --output_model_file (-M) [unknown]
              Output for trained HMM.

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.