/Java/How can I do tf idf weighting in scikit learn?

How can I do tf idf weighting in scikit learn?

>>> from sklearn.feature_extraction.text import TfidfVectorizer
>>> corpus = [
...     'This is the first document.',
...     'This document is the second document.',
...     'And this is the third one.',
...     'Is this the first document?',
... ]
>>> vectorizer = TfidfVectorizer()
>>> X = vectorizer.fit_transform(corpus)
>>> print(vectorizer.get_feature_names())
['and', 'document', 'first', 'is', 'one', 'second', 'the', 'third', 'this']
>>> print(X.shape)
(4, 9)

Source: stackoverflow.com

Similar codes

0 vote217 views1 answer
Cask 'java' is unreadable: undefined method `release' for OS::Mac:Modul
Java
-1 vote186 views2 answers
Arraylist remove value in java
Java
2 votes189 views1 answer
Javafx stackpane set position
Java
0 vote184 views1 answer
Print colored text java
Java
0 vote191 views1 answer
Create and populate list one line java
Java
9 votes210 views2 answers
Change port in spring boot
Java
23 votes194 views1 answer
Bootstrap messages red
Java
3 votes192 views1 answer
Ocha in japanese
Java
-1 vote258 views1 answer
Get spring application context
Java Spring
1 vote206 views6 answers
This version of the Android Support plugin for IntelliJ IDEA (or Android Studio) cannot open this project, please retry with version 4.2 or newer.
Java