title: TfIdf learning rate / document weight
body: <p>I'm currently using sklearn to build an application that compares a given document with other documents, looking for similarity.</p>
  
  <p>When using other techniques like LSA, I know that I can tune the learning rate so that older documents are forgot or less important. Is there some way for me to do something similar using TfIdf? It would be better if I could define a weight proportional to the "date" of a document.</p>
  
  <p>I was thinking on applying some sort of slowly decaying exponential function on the relative date of the document, and multiplying this to the final cosine score of the similarity. Is this a good approach?</p>