Breaking News: Grepper is joining You.com. Read the official announcement!

TfidfVectorizer use

Blushing Buzzard answered on April 11, 2022 Popularity 10/10 Helpfulness 2/10

answer TfidfVectorizer use

TfidfVectorizer use

Comment

Text1 = “Natural Language Processing is a subfield of AI”
tag1 = "NLP"

Text2 = “Computer Vision is a subfield of AI”
tag2 = "CV"


from sklearn.feature_extraction.text import TfidfVectorizer as tf_idf
import pandas as pd
tfidf = tf_idf(norm = None)
tfidf.fit([Text1, Text2])
x= tfidf.transform([Text1]).toarray()
y= tfidf.transform([Text2]).toarray()
columns = tfidf.get_feature_names()
df1 = pd.DataFrame(x, columns= columns, index= ["Text1"])
df2 = pd.DataFrame(y, columns= columns, index= ["Text2"])
df = pd.concat([df1,df2])
df["tag"] = ["NLP", "CV"]
df

Popularity 10/10 Helpfulness 2/10 Language python

Source: Grepper

Tags: python

Link to this answer
Share Copy Link

Contributed on Apr 11 2022

Blushing Buzzard

0 Answers Avg Quality 2/10

Continue with Google

By continuing, I agree that I have read and agree to Greppers's Terms of Service and Privacy Policy.

TfidfVectorizer use

Contents

More Related Answers

TfidfVectorizer use

Grepper

Documentation

Social

Legal

Contact

Oops, You will need to install Grepper and log-in to perform this action.