Find the tf-idf score of specific words in documents using sklearn
@kinkajou, No, TF and IDF are not same but they belong to the same algorithm- TF-IDF, i.e Term frequency Inverse document Frequency
I have code that runs basic TF-IDF vectorizer on a collection of documents, returning a sparse matrix of D X F where D is the number of documents and F is the number of terms. No problem.
But how do I find the TF-IDF score of a specific term in the document? i.e. is there some sort of dictionary between terms (in their textual representation) and their position in the resulting sparse matrix?