Man page - mlpack_hmm_generate(1)
Packages contains this manual
- mlpack_fastmks(1)
- mlpack_mean_shift(1)
- mlpack_hmm_generate(1)
- mlpack_local_coordinate_coding(1)
- mlpack_sparse_coding(1)
- mlpack_preprocess_scale(1)
- mlpack_kmeans(1)
- mlpack_linear_svm(1)
- mlpack_preprocess_split(1)
- mlpack_softmax_regression(1)
- mlpack_hmm_train(1)
- mlpack_nca(1)
- mlpack_range_search(1)
- mlpack_radical(1)
- mlpack_gmm_generate(1)
- mlpack_cf(1)
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- mlpack_gmm_probability(1)
- mlpack_emst(1)
- mlpack_dbscan(1)
- mlpack_nbc(1)
- mlpack_preprocess_one_hot_encoding(1)
- mlpack_lsh(1)
- mlpack_knn(1)
- mlpack_kde(1)
- mlpack_hoeffding_tree(1)
- mlpack_adaboost(1)
- mlpack_hmm_loglik(1)
- mlpack_nmf(1)
- mlpack_pca(1)
- mlpack_bayesian_linear_regression(1)
- mlpack_hmm_viterbi(1)
- mlpack_preprocess_describe(1)
- mlpack_decision_tree(1)
- mlpack_krann(1)
- mlpack_det(1)
- mlpack_lars(1)
- mlpack_preprocess_binarize(1)
- mlpack_logistic_regression(1)
- mlpack_gmm_train(1)
- mlpack_perceptron(1)
- mlpack_preprocess_imputer(1)
- mlpack_kernel_pca(1)
- mlpack_kfn(1)
- mlpack_linear_regression(1)
- mlpack_approx_kfn(1)
apt-get install mlpack-bin
Manual
mlpack_hmm_generate
NAMESYNOPSIS
DESCRIPTION
REQUIRED INPUT OPTIONS
OPTIONAL INPUT OPTIONS
OPTIONAL OUTPUT OPTIONS
ADDITIONAL INFORMATION
NAME
mlpack_hmm_generate - hidden markov model (hmm) sequence generator
SYNOPSIS
mlpack_hmm_generate -l int -m unknown [ -s int ] [ -t int ] [ -V bool ] [ -o unknown ] [ -S unknown ] [ -h -v ]
DESCRIPTION
This utility takes an already-trained HMM, specified as the ’ --model_file ( -m )’ parameter, and generates a random observation sequence and hidden state sequence based on its parameters. The observation sequence may be saved with the ’ --output_file ( -o )’ output parameter, and the internal state sequence may be saved with the ’ --state_file ( -S )’ output parameter.
The state to start the sequence in may be specified with the ’ --start_state ( -t )’ parameter.
For example, to generate a sequence of length 150 from the HMM ’hmm.bin’ and save the observation sequence to ’observations.csv’ and the hidden state sequence to ’states.csv’, the following command may be used:
$ mlpack_hmm_generate --model_file hmm.bin --length 150 --output_file observations.csv --state_file states.csv
REQUIRED INPUT OPTIONS
--length (-l) [ int ]
Length of sequence to generate.
--model_file (-m) [ unknown ]
Trained HMM to generate sequences with.
OPTIONAL INPUT OPTIONS
--help (-h) [ bool ]
Default help info.
--info [string]
Print help on a specific option. Default value ’’.
--seed (-s) [ int ]
Random seed. If 0, ’std::time(NULL)’ is used. Default value 0.
--start_state (-t) [ int ]
Starting state of sequence. Default value 0.
--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_file
(
-o
) [
unknown
] Matrix to save observation
sequence to.
--state_file (-S) [
unknown
]
Matrix to save hidden state sequence to.
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.