Provided by: mlpack-bin_3.0.4-1_amd64
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.
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] 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.
OPTIONAL OUTPUT OPTIONS
--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 http://www.mlpack.org or included with your distribution of mlpack.