#include <mlpack/prereqs.hpp>#include <mlpack/core/util/io.hpp>#include <mlpack/core/util/mlpack_main.hpp>#include "hmm.hpp"#include "hmm_model.hpp"#include <mlpack/methods/gmm/gmm.hpp>#include <mlpack/methods/gmm/diagonal_gmm.hpp>
Include dependency graph for hmm_loglik_main.cpp:
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Classes | |
| struct | Loglik |
Functions | |
| BINDING_NAME ("Hidden Markov Model (HMM) Sequence Log-Likelihood") | |
| BINDING_SHORT_DESC ("A utility for computing the log-likelihood of a sequence for Hidden Markov" " Models (HMMs). Given a pre-trained HMM and an observation sequence, this" " computes and returns the log-likelihood of that sequence being observed " "from that HMM.") | |
| BINDING_LONG_DESC ("This utility takes an already-trained HMM, specified with the "+PRINT_PARAM_STRING("input_model")+" parameter, and evaluates the " "log-likelihood of a sequence of observations, given with the "+PRINT_PARAM_STRING("input")+" parameter. The computed log-likelihood is" " given as output.") | |
| BINDING_EXAMPLE ("For example, to compute the log-likelihood of the sequence "+PRINT_DATASET("seq")+" with the pre-trained HMM "+PRINT_MODEL("hmm")+", the following command may be used: " "\"+PRINT_CALL("hmm_loglik", "input", "seq", "input_model", "hmm")) | |
| BINDING_SEE_ALSO ("@hmm_train", "#hmm_train") | |
| BINDING_SEE_ALSO ("@hmm_generate", "#hmm_generate") | |
| BINDING_SEE_ALSO ("@hmm_viterbi", "#hmm_viterbi") | |
| BINDING_SEE_ALSO ("Hidden Mixture Models on Wikipedia", "https://en.wikipedia.org/wiki/Hidden_Markov_model") | |
| BINDING_SEE_ALSO ("mlpack::hmm::HMM class documentation", "@doxygen/classmlpack_1_1hmm_1_1HMM.html") | |
| PARAM_MATRIX_IN_REQ ("input", "File containing observations,", "i") | |
| PARAM_MODEL_IN_REQ (HMMModel, "input_model", "File containing HMM.", "m") | |
| PARAM_DOUBLE_OUT ("log_likelihood", "Log-likelihood of the sequence.") | |
Detailed Description
Compute the log-likelihood of a given sequence for a given HMM.
mlpack is free software; you may redistribute it and/or modify it under the terms of the 3-clause BSD license. You should have received a copy of the 3-clause BSD license along with mlpack. If not, see http://www.opensource.org/licenses/BSD-3-Clause for more information.
