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################################################################################
# Copyright (C) 2011-2013 Jaakko Luttinen
#
# This file is licensed under the MIT License.
################################################################################
import numpy as np
from bayespy.utils import random
from bayespy import nodes
from bayespy.inference.vmp.vmp import VB
def run(M=30, D=5):
# Generate data
y = np.random.randint(D, size=(M,))
# Construct model
p = nodes.Dirichlet(1*np.ones(D),
name='p')
z = nodes.Categorical(p,
plates=(M,),
name='z')
# Observe the data with randomly missing values
mask = random.mask(M, p=0.5)
z.observe(y, mask=mask)
# Run VB-EM
Q = VB(p, z)
Q.update()
# Show results
z.show()
p.show()
if __name__ == '__main__':
run()
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