Wednesday, 2 July 2014

Explanation for Extending Stemming using NLTK

Notebook
In [2]: 
from sklearn.feature_extraction.text import CountVectorizer
cv = CountVectorizer()
analyzer = cv.build_analyzer()

import nltk.stem
english_stemmer = nltk.stem.SnowballStemmer('english')

doc = "A cook cooks delicious meals"
print([english_stemmer.stem(w) for w in analyzer(doc)])

[u'cook', u'cook', u'delici', u'meal']
In []:
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