/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

4 votes354 views2 answers
Import class java
Java
2 votes331 views1 answer
Java swing button on click
Java
0 vote345 views2 answers
Remove autofill edittext android
Java
0 vote340 views1 answer
Algorithms - filtering
Java
3 votes367 views3 answers
How to change my file into binary data using java
Java
4 votes348 views1 answer
Spring load config value in variable
Java
1 vote363 views1 answer
Can you use java in unity
Java
0 vote341 views1 answer
Initialize list in java in one line
Java
1 vote345 views1 answer
An enclosing instance that contains Outer.Inner is required
Java
4 votes370 views2 answers
Java command line arguments
Java