Question on running fitlda
1 Ansicht (letzte 30 Tage)
Ältere Kommentare anzeigen
Stephen Bruestle
am 6 Dez. 2018
Kommentiert: Stephen Bruestle
am 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);
0 Kommentare
Akzeptierte Antwort
Christopher Creutzig
am 10 Dez. 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 Kommentare
Kai Friedrich
am 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!
Weitere Antworten (0)
Siehe auch
Kategorien
Mehr zu Data Distribution Plots finden Sie in Help Center und File Exchange
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!