I have a TF-IDF matrix of a dataset of products:
tfidf = TfidfVectorizer().fit_transform(words)
where words is a list of descriptions. This produces a 69258x22024 matrix.
Now I want to find cosine similarities between a new product and the ones in the matrix, as I need to find the 10 most similar products to it. I vectorize it using the same method above.
However, I cannot multiply the matrices because their sizes are different (the new one would be like 6 words, so a 1x6 matrix), so I need to make a TFIDFVectorizer with the number of columns as the original one.
How do I do it?