Hi, I am implementing LDA with pymc3. I referred to the code for pymc import numpy as np import pymc as pm K = 2 # number of topics V = 4 # number of words D = 3 # number of documents data = np.array([[1, 1, 1, 1], [1, 1, 1, 1], [0, 0, 0, 0]]) alpha = np.ones(K) beta = np.ones(V+1) theta = pm.…

Metropolis does not generate valid proposal for Categorical Random Variables, see https://github.com/pymc-devs/pymc3/issues/3023#issuecomment-396288202

LDA implementation with pymc3

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gaddamanil16 July 17, 2018, 5:58pm 6

But using tr = pm.sample(1000,chains = 1) works. I am not able to understand which one works in what way?

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LDA implementation with pymc3

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