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scikit-learn 버전 0.14.1을 사용하여 tf-idf를 계산하려고했습니다.__init __()에 예상치 못한 키워드 인수가 있습니다. 'stop_words'
Traceback (most recent call last):
File "tfidf.py", line 12, in <module>
vectorizer = CountVectorizer(stop_words = stopWords)
TypeError: __init__() got an unexpected keyword argument 'stop_words'
, 저 좀 도와주세요 'STOP_WORDS'의 문제가 무엇인지 이해하지 않습니다
from sklearn.feature_extraction.text import CountVectorizer
from sklearn.feature_extraction.text import TfidfTransformer
from nltk.corpus import stopwords
import numpy as np
import numpy.linalg as LA
train_set = ["The sky is blue.", "The sun is bright."] #Documents
test_set = ["The sun in the sky is bright sun."] #Query
stopWords = stopwords.words('english')
vectorizer = CountVectorizer(stop_words = stopWords)
#print vectorizer
transformer = TfidfTransformer()
#print transformer
trainVectorizerArray = vectorizer.fit_transform(train_set).toarray()
testVectorizerArray = vectorizer.transform(test_set).toarray()
print 'Fit Vectorizer to train set', trainVectorizerArray
print 'Transform Vectorizer to test set', testVectorizerArray
transformer.fit(trainVectorizerArray)
print
print transformer.transform(trainVectorizerArray).toarray()
transformer.fit(testVectorizerArray)
print
tfidf = transformer.transform(testVectorizerArray)
print tfidf.todense()
나는이 오류가 발생했습니다 : 여기 내 코드는?