Man page - mlpack_hmm_train(1)
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apt-get install mlpack-bin
Manual
mlpack_hmm_train
NAMESYNOPSIS
DESCRIPTION
REQUIRED INPUT OPTIONS
OPTIONAL INPUT OPTIONS
OPTIONAL OUTPUT OPTIONS
ADDITIONAL INFORMATION
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.