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From "Bae, Jae Hyeon" <>
Subject Question about LDA parameter estimation
Date Thu, 10 Mar 2011 06:28:09 GMT

I am studying LDA algorithm for my statistics project. The goal is fully
understanding LDA algorithms and statistical concepts behind that and
analyze implementation. I've chosen Mahout LDA implementation because it's
scalable and well-documented.

According to the original paper written by Blei, Ng, Jordan,
parameters(alpha, beta) would be estimated with variational EM method. But I
can't find any numerical methods to optimize those parameters. In Mahout
implementation, alpha is topic smoothing input by user, beta is just
P(word|topic), not estimated.

I think that this implementation has a basic assumption. I want to know
whether there was specific reason to implement like this without parameter

Thank you

Best, Jay

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