I was looking at the documentation for the LsiModel and could not tell if/where a weighting scheme is applied to document vectors.
It seems like the following lines are where the main transformations of LSA take place, and no weighting occurs:
if not scipy.sparse.issparse(docs):
docs = matutils.corpus2csc(docs)
ut, s, vt = sparsesvd.sparsesvd(docs, k + 30)
However most definitions of the LSA algorithm include a step where some weighting scheme, like TF-IDF is applied. Do I have to apply gensim.models.TfidfModel to preprocess my corpus before training an LsiModel to fit this definition of LSA?
And out of curiosity if the LsiModel does not implicitly have a weighting step - why?