I am trying to train a model for supervised learning for Hidden Markov Model (HMM)and test it on a set of observations however, keep getting this error. The goal is to predict the state based on the observations. How can I fix this and how can I view the transition matrix?
The version for Pomegranate is 0.14.4 Trying this from the source: https://github.com/jmschrei/pomegranate/issues/1005
from pomegranate import *
import numpy as np
# Supervised method that calculates the transition matrix:
d1 = State(UniformDistribution.from_samples([3.243221498397177, 3.210684537495482, 3.227662201472816,
3.286410817416738, 3.290573650708864, 3.286058136226862, 3.266480693857006]))
d2 = State(UniformDistribution.from_samples([3.449282367485096, 1.97317859465635, 1.897551432353011,
3.454609351559659, 3.127357456033111, 1.779308337786426, 3.802891929694426, 3.359766157565077, 2.959428499979418]))
d3 = State(UniformDistribution.from_samples([1.892812118441474, 1.589353118681066, 2.09269978285637,
2.104391496570218, 1.656771181054144]))
model = HiddenMarkovModel()
model.add_states(d1, d2, d3)
# print(model.to_json())
model.bake()
model.fit([3.2, 6.7, 10.55], labels=[1, 2, 3], algorithm='labeled')
all_pred = model.predict([2.33, 1.22, 1.4, 10.6])
Error:
File "C:\Program Files\JetBrains\PyCharm Community Edition 2021.2\plugins\python-ce\helpers\pydev\_pydev_bundle\pydev_umd.py", line 198, in runfile
pydev_imports.execfile(filename, global_vars, local_vars) # execute the script
File "C:\Program Files\JetBrains\PyCharm Community Edition 2021.2\plugins\python-ce\helpers\pydev\_pydev_imps\_pydev_execfile.py", line 18, in execfile
exec(compile(contents+"\n", file, 'exec'), glob, loc)
File "C:/Users/", line 774, in <module>
model.bake()
File "pomegranate/hmm.pyx", line 1047, in pomegranate.hmm.HiddenMarkovModel.bake
UnboundLocalError: local variable 'dist' referenced before assignment
pomegranatelibrary. Talk to its authors, not to us.pomegranate, I'd want to know exactly which version of the library you're running so I'm not wasting my time looking at the wrong source. It can't be the latest one -- in the tip of the main branch, line 1047 is a comment.distribution=None. Still, it's a pomegranate problem that they don't raise a useful/meaningful exception in that case)