Provided by: mlpack-bin_3.0.4-1_amd64 bug


       mlpack_hmm_train - hidden markov model (hmm) training


        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]


       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.


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


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

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

       --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 | 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.


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


       For  further  information,  including  relevant papers, citations, and theory, consult the
       documentation found at or included with your distribution of mlpack.