cv = sklearn.feature_extraction.text.CountVectorizer(vocabulary=['hot',
    'cold', 'old'])
cv.fit_transform(['pease porridge hot', 'pease porridge cold',
    'pease porridge in the pot', 'nine days old']).toarray()
Can I use CountVectorizer in scikit-learn to count frequency of documents that were not used to extract the tokens?