class GHMM - this class is non-functional and was meant to implement a Generalize Hidden Markov Model (aka Semi Hidden Markov HMM).
Definition at line 22 of file GHMM.h.
Public Member Functions | |
| CGHMM () | |
| virtual | ~CGHMM () |
| virtual bool | train (CFeatures *data=NULL) |
| virtual int32_t | get_num_model_parameters () |
| virtual float64_t | get_log_model_parameter (int32_t param_num) |
| virtual float64_t | get_log_derivative (int32_t param_num, int32_t num_example) |
| virtual float64_t | get_log_likelihood_example (int32_t num_example) |
| float64_t get_log_derivative | ( | int32_t | param_num, | |
| int32_t | num_example | |||
| ) | [virtual] |
get logarithm of one example's derivative's likelihood
| param_num | which example's param | |
| num_example | which example |
Implements CDistribution.
| float64_t get_log_likelihood_example | ( | int32_t | num_example | ) | [virtual] |
get logarithm of one example's likelihood
| num_example | which example |
Implements CDistribution.
| float64_t get_log_model_parameter | ( | int32_t | param_num | ) | [virtual] |
get logarithm of given model parameter
| param_num | which param |
Implements CDistribution.
| int32_t get_num_model_parameters | ( | ) | [virtual] |
| bool train | ( | CFeatures * | data = NULL |
) | [virtual] |
learn distribution
| data | training data (parameter can be avoided if distance or kernel-based classifiers are used and distance/kernels are initialized with train data) |
Implements CDistribution.
