[FIXED] What is the difference between CountVectorizer+TfidfTransformer and TfidfVectorizer

Issue

To apply ML algorithm on text, it has to be represented numerically. Some ways to do this using sklearn are:

1. CountVectorizer

2. CountVectorizer + TfidfTransformer

3. TfidfVectorizer

What is the difference between CountVectorizer+TfidfTransformer and TfidfVectorizer?

Solution

None, see the top of the documentation page:

sklearn.feature_extraction.text.TfidfVectorizer
...
Equivalent to CountVectorizer followed by TfidfTransformer. 

Answered By - mbatchkarov