EMLDAOptimizer

final class EMLDAOptimizer extends LDAOptimizer

:: DeveloperApi ::

Optimizer for EM algorithm which stores data + parameter graph, plus algorithm parameters.

Currently, the underlying implementation uses Expectation-Maximization (EM), implemented according to the Asuncion et al. (2009) paper referenced below.

References:

• Original LDA paper (journal version): Blei, Ng, and Jordan. "Latent Dirichlet Allocation." JMLR, 2003.
• This class implements their "smoothed" LDA model.
• Paper which clearly explains several algorithms, including EM: Asuncion, Welling, Smyth, and Teh. "On Smoothing and Inference for Topic Models." UAI, 2009.
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@Since( "1.4.0" ) ()
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LDAOptimizer.scala
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