Joseph K. Bradley created SPARK-5564:
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Summary: Support sparse LDA solutions
Key: SPARK-5564
URL: https://issues.apache.org/jira/browse/SPARK-5564
Project: Spark
Issue Type: Improvement
Components: MLlib
Affects Versions: 1.3.0
Reporter: Joseph K. Bradley
Latent Dirichlet Allocation (LDA) currently requires that the priors’
concentration parameters be > 1.0. It should support values > 0.0, which
should encourage sparser topics (phi) and document-topic distributions (theta).
For EM, this will require adding a projection to the M-step, as in: Vorontsov
and Potapenko. "Tutorial on Probabilistic Topic Modeling : Additive
Regularization for Stochastic Matrix Factorization." 2014.
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