/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 votes406 views2 answers
Java import decimalformat
Java
5 votes403 views2 answers
How to add elements in array in java using for loop
Java
17 votes276 views7 answers
Could not find driver (sql: select * from information_schema.tables where table_schema = laravel and table_name = migrations and table_type = 'base table')
Java
0 vote352 views1 answer
Dynamic fib
Java
9 votes527 views2 answers
Change the default port in spring boot codegrepper
Java Spring
0 vote373 views1 answer
Leer XML java
Java
0 vote331 views1 answer
Android get app build name
Java
1 vote416 views1 answer
Javafx location is required
Java
0 vote372 views1 answer
OCA Exam Questions
Java
1 vote381 views1 answer
How to write sensor data into file android studio
Java