You are provided with four documents, numbered 1 to 4, each with a single sentence of text. Determine the identifier of the document which is the most similar to the first document, as computed according to the TF-IDF scores.

My name is Ankit,
Ankit name is very famous,
Ankit like his name
India has a lot of beautiful cities

Output the integer (which may be either 2 or 3 or 4), leaving no leading or trailing spaces.

import numpy as npfrom sklearn.feature_extraction.text import TfidfVectorizervect = TfidfVectorizer(min_df=1)tfidf = vect.fit_transform(["My name is Ankit","Ankit name is very famous","Ankit like his name","India has a lot of beautiful cities"])print ((tfidf * tfidf.T).A)