mlpack_hmm_train(1)

1mlpack_hmm_train(1)         General Commands Manual        mlpack_hmm_train(1)
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NAME

6       mlpack_hmm_train - hidden markov model (hmm) training
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SYNOPSIS

9        mlpack_hmm_train [-h] [-v]
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DESCRIPTION

12       This  program  allows a Hidden Markov Model to be trained on labeled or
13       unlabeled data. It support three types of HMMs: discrete HMMs, Gaussian
14       HMMs, or GMM HMMs.
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16       Either  one  input sequence can be specified (with --input_file), or, a
17       file containing files in which  input  sequences  can  be  found  (when
18       --input_file and --batch are used together). In addition, labels can be
19       provided in the file specified by  --labels_file,  and  if  --batch  is
20       used, the file given to --labels_file should contain a list of files of
21       labels  corresponding  to  the  sequences  in   the   file   given   to
22       --input_file.
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24       The  HMM is trained with the Baum-Welch algorithm if no labels are pro‐
25       vided.  The tolerance of the Baum-Welch algorithm can be set  with  the
26       --tolerance  option. By default, the transition matrix is randomly ini‐
27       tialized and the emission distributions  are  initialized  to  fit  the
28       extent of the data.
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30       Optionally,  a  pre-created  HMM  model  can be used as a guess for the
31       transition matrix and emission probabilities; this is specifiable  with
32       --model_file.
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REQUIRED INPUT OPTIONS

35       --input_file (-i) [string]
36              File containing input observations.
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38       --type (-t) [string]
39              Type of HMM: discrete | gaussian | gmm.
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OPTIONAL INPUT OPTIONS

42       --batch (-b)
43              If true, input_file (and if passed, labels_file) are expected to
44              contain a list of files to use as  input  observation  sequences
45              (and label sequences).
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47       --gaussians (-g) [int]
48              Number  of gaussians in each GMM (necessary when type is 'gmm').
49              Default value 0.
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51       --help (-h)
52              Default help info.
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54       --info [string]
55              Get help on a specific module or option.  Default value ''.
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57       --labels_file (-l) [string]
58              Optional file of  hidden  states,  used  for  labeled  training.
59              Default value ''.
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61       --model_file (-m) [string]
62              Pre-existing HMM model file. Default value ''.
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64       --seed (-s) [int]
65              Random seed. If 0, 'std::time(NULL)' is used.  Default value 0.
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67       --states (-n) [int]
68              Number  of hidden states in HMM (necessary, unless model_file is
69              specified). Default value
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71              0.
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74       --tolerance (-T) [double]
75              Tolerance of the Baum-Welch algorithm. Default value 1e-05.
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77       --verbose (-v)
78              Display informational messages and the full list  of  parameters
79              and timers at the end of execution.
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81       --version (-V)
82              Display the version of mlpack.
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OPTIONAL OUTPUT OPTIONS

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

90       For further information, including relevant papers, citations, and the‐
91       ory, For further information, including relevant papers, citations, and
92       theory, consult the documentation  found  at  http://www.mlpack.org  or
93       included    with    your    consult    the   documentation   found   at
94       http://www.mlpack.org or included with  your  DISTRIBUTION  OF  MLPACK.
95       DISTRIBUTION OF MLPACK.
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99                                                           mlpack_hmm_train(1)