In3x,net,watch,14zwhrd6,dildo,18 • Free Access

from sklearn.feature_extraction.text import CountVectorizer, TfidfTransformer

# TF-IDF transformer tfidf = TfidfTransformer() tfidf_features = tfidf.fit_transform(count_features) in3x,net,watch,14zwhrd6,dildo,18

# Vectorizer to convert text into a matrix of token counts vectorizer = CountVectorizer() count_features = vectorizer.fit_transform(data) from sklearn