gensim.models.LdaMulticore.update¶

LdaMulticore.update(corpus, chunks_as_numpy=False)[source]¶

Train the model with new documents, by EM-iterating over corpus until the topics converge (or until the maximum number of allowed iterations is reached). corpus must be an iterable (repeatable stream of documents),

The E-step is distributed into the several processes.

This update also supports updating an already trained model (self) with new documents from corpus; the two models are then merged in proportion to the number of old vs. new documents. This feature is still experimental for non-stationary input streams.

For stationary input (no topic drift in new documents), on the other hand, this equals the online update of Hoffman et al. and is guaranteed to converge for any decay in (0.5, 1.0>.