hidden semi markov model python from scratch
posteriormodel.add_data(data,trunc=60)hidden semi markov model python from scratch
posteriormodel.add_data(data,trunc=60)hidden semi markov model python from scratch
import pyhsmm
import pyhsmm.basic.distributions as distributions
obs_dim = 2
Nmax = 25
obs_hypparams = {'mu_0':np.zeros(obs_dim),
'sigma_0':np.eye(obs_dim),
'kappa_0':0.3,
'nu_0':obs_dim+5}
dur_hypparams = {'alpha_0':2*30,
'beta_0':2}
obs_distns = [distributions.Gaussian(**obs_hypparams) for state in range(Nmax)]
dur_distns = [distributions.PoissonDuration(**dur_hypparams) for state in range(Nmax)]
posteriormodel = pyhsmm.models.WeakLimitHDPHSMM(
alpha=6.,gamma=6., # better to sample over these; see concentration-resampling.py
init_state_concentration=6., # pretty inconsequential
obs_distns=obs_distns,
dur_distns=dur_distns)Copyright © 2021 Codeinu
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