NLTK's snowball extract stemming

The most important application scenario in machine learning is the automatic classification of machines, and the key to classification is stemming. So we're going to use the snowball. Here's a look at two ways to extract stems from snowball.

Two methods:

Method One:

>>> from NLTK import Snowballstemmer
>>> Snowballstemmer.languages # See which languages is supported
(' Danish ', ' Dutch ', ' 中文版 ', ' Finnish ', ' French ', ' German ', ' Hungarian ',
' Italian ', ' Norwegian ', ' Porter ', ' Portuguese ', ' Romanian ',
' Russian ', ' Spanish ', ' Swedish ')
>>> stemmer = Snowballstemmer ("German") # Choose a language
>>> stemmer.stem (U "Autobahnen") # Stem a word
U ' Autobahn '
But when you know the language scene you are using, you can call it directly using the following method:
Method Two:
>>> PS = Nltk.stem.snowball.PortugueseStemmer ()
>>> ps.stem (' Celular ')
U ' Celul '
>>> ps.stem (' Celular ')
U ' Celul '

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