Results of Hidden Markov Models for a single class. More...
#include <xmmHmmResults.hpp>
Public Attributes | |
| double | instant_likelihood |
| Instantaneous likelihood. More... | |
| double | log_likelihood |
| Cumulative log-likelihood computed on a sliding window. More... | |
| std::vector< float > | output_values |
| Predicted Output parameter vector (only used in regression mode) More... | |
| std::vector< float > | output_covariance |
| Predicted Output covariance associated with the generated parameter vector (only used in regression mode) More... | |
| double | progress |
| Estimated time progression. More... | |
| double | exit_likelihood |
| Likelihood to exit the gesture on the next time step. More... | |
| double | exit_ratio |
| Likelihood to exit the gesture on the next time step (normalized -/- total likelihood) More... | |
| unsigned int | likeliest_state |
| Index of the likeliest state. More... | |
Results of Hidden Markov Models for a single class.
| double xmm::ClassResults< HMM >::exit_likelihood |
Likelihood to exit the gesture on the next time step.
| double xmm::ClassResults< HMM >::exit_ratio |
Likelihood to exit the gesture on the next time step (normalized -/- total likelihood)
| double xmm::ClassResults< HMM >::instant_likelihood |
Instantaneous likelihood.
| unsigned int xmm::ClassResults< HMM >::likeliest_state |
Index of the likeliest state.
| double xmm::ClassResults< HMM >::log_likelihood |
Cumulative log-likelihood computed on a sliding window.
| std::vector<float> xmm::ClassResults< HMM >::output_covariance |
Predicted Output covariance associated with the generated parameter vector (only used in regression mode)
| std::vector<float> xmm::ClassResults< HMM >::output_values |
Predicted Output parameter vector (only used in regression mode)
| double xmm::ClassResults< HMM >::progress |
Estimated time progression.
The time progression is computed as the centroid of the state probability distribution estimated by the forward algorithm