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 as returned by
Any other options, from the official documentation.
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.