I have used gensim.utils.simple_preprocess(str(sentence) to create a dictionary of words that I want to use for topic modelling. However, this is also filtering important numbers (house resolutions, bill no, etc) that I really need. How did I overcome this? Possibly by replacing digits with their word form. How do i go about it, though?
How do i retain numbers while preprocessing data using gensim in python?
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You don't have to use
simple_preprocess()- it's not doing much, it's not that configurable or sophisticated, and typically the other Gensim algorithms just need lists-of-tokens.So, choose your own tokenization - which in some cases, depnding on your source data, could be as simple as a
.split()on whitespace.If you want to look at what
simple_preprocess()does, as a model, you can view its Python source at:https://github.com/RaRe-Technologies/gensim/blob/351456b4f7d597e5a4522e71acedf785b2128ca1/gensim/utils.py#L288