Is it possible to use countvectorizer with StandardScaler?

Question

I am using countvectorizer to extract features, and I am wondering if I can scale the features. With the code below I am wondering if I can do some scaling using StandardScaler.

from sklearn.feature_extraction.text import CountVectorizer
vectorizer = CountVectorizer()
x_training=vectorizer.fit_transform(df ['var'])

Answer 1

as CountVectorizer creates a sparse matrix of features, the StandardScalar function from sklearn will throw an exception as it does'nt take sparse matrix.

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