CODEWITHSUNDEEP
pythonhidden-markov-modelshmmlearn
mrt
mrt

Reputation: 339

Can't understand the difference between these parameters in GaussianHMM()

Can someone explain me the difference between the parameters transmat_ andtransmat_prior, when I setup the model ( e.g. GaussianHMM() in hmmlearn.hmm )?

class hmmlearn.hmm.GaussianHMM( n_components    =  1,
                                covariance_type = 'diag',
                                min_covar       =  0.001,
                                startprob_prior =  1.0,
                                transmat_prior  =  1.0,
                                means_prior     =  0,
                                means_weight    =  0,
                                covars_prior    =  0.01,
                                covars_weight   =  1,
                                algorithm       = 'viterbi',
                                random_state    =  None,
                                n_iter          = 10,
                                tol             =  0.01,
                                verbose         =  False,
                                params          = 'stmc',
                                init_params     = 'stmc'
                                )

Does the same explanation also hold for the parameters startprob_prior and startbrob_?

Upvotes: 1

Views: 905

Answers (1)

Eskapp
Eskapp

Reputation: 3645

In my understanding, transmat_prior is the initial value for the transition matrix that you can specify (it will be used for initializing the iterative parameter estimation algorithm). It is a parameter of the class.

transmat_ is an attribute of an object of the class GaussianHMM, it gives the values of the transition matrix after training. It is not something you input yourself but a result of the estimation process.

Upvotes: 2

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