How does Doc2Vec treat numerical data which is a part of text data? I have data containing both numbers and raw text related differently like:


The power of diesel generator is 15kva. I need a single phase generator.
Three phase generator required of 140 kva.
Need 70g/m^2 GSM a4 size copier paper.


I removed the numerical data and trained a classifier on vector obtained from Doc2Vec and got around 80% accuracy.

Is there a way to take in account the numbers (here 15,140,70) involved in text while creating a doc2vec vector? or if there is any way to take in account these numbers in order to improve on the accuracy?
If you are passing in the numbers as a string type Doc2Vec should just accept these as part of the vocabulary without an issue. Have you tried running the Doc2Vec training with the numbers still included? 

One way to solve the issue if you can't just pass the values in as is is to give them a unique identifier (e.g. &lt; NUM >). It shouldn't matter what the value is as Doc2Vec should in theory not be able to draw any information (and really shouldn't) from that. Instead if you teach it when a number occurs in a document (by using the identifier) that might improve accuracy.