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.