model_rp.Rd
Reduce vector space dimensionality. This is a very efficient (both memory- and CPU-friendly) approach to approximating TfIdf distances between documents, by throwing in a little randomness.
model_rp(corpus, ...) # S3 method for wrapped model_rp(corpus, ...) # S3 method for gensim.interfaces.TransformedCorpus model_rp(corpus, ...) load_rp(file)
corpus | Corpus as returned by |
---|---|
... | Any other options, from the official documentation. |
file | Path to a saved model. |
Target dimensionality (num_topics
) of 200–500 is recommended as a “golden standard” https://dl.acm.org/citation.cfm?id=1458105.