Question on running fitlda
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Stephen Bruestle
on 6 Dec 2018
Commented: Stephen Bruestle
on 11 Jun 2020
I want to run fitlda, with the following specification:
* use Griffiths and Steyvers (2004) Gibbs Sampling algorithm for LDA as they ran it,
* 12 topics (i.e. K=12),
* a symmetric alpha of 50/K (no updating),
* a symmetric beta of .01 (no updating), and
* exactly 2000 iterations (without early termination).
Would that be:
numTopics = 12;
mdl = fitlda(bag,numTopics,'Verbose',1,'InitialTopicConcentration',50,'FitTopicConcentration',false,'WordConcentration',.01,'LogLikelihoodTolerance',0,'IterationLimit',2000);
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Accepted Answer
Christopher Creutzig
on 10 Dec 2018
Gibbs sampling involves stochastic elements (i.e., a pseudorandom number generator), meaning reproducing exactly the results of the 2004 paper will require using their code and their rng settings. (Which is also why in degenerate cases, you do get substantially different answers for multiple fitlda calls.)
Without looking up the definition of β in the original paper, I'm not sure if you want to set 'WordConcentration',.01 or 'WordConcentration',.01*bag.NumWords.
Other than that, the call looks like it should do what you ask, yes.
3 Comments
Kai Friedrich
on 11 Jun 2020
Hey Stephen,
I am trying to do the same thing.
Great answer for the beta parameter.
What about alpha?
Is sufficient to just insert 50, when I want my alpha parameter in MATLAB to be 50/K?
Thanks!
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