from sklearn.feature_extraction.text import HashingVectorizer
list of text documents
text = ["The quick brown fox jumped over the lazy dog."]
create the transform
vectorizer = HashingVectorizer(n_features=20)
encode document
vector = vectorizer.transform(text)
summarize encoded vector
print(vector.shape)
print(vector.toarray())
from sklearn.feature_extraction.text import HashingVectorizer
list of text documents
text = ["The quick brown fox jumped over the lazy dog."]
create the transform
vectorizer = HashingVectorizer(n_features=20)
encode document
vector = vectorizer.transform(text)
summarize encoded vector
print(vector.shape)
print(vector.toarray())