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我是sklearn管道的新手,并从sklearn文档研究它。我用它在movie review数据的情绪分析。数据包含两列,第一个为class
,第二个为text
。sklearn管道不工作
input_file_df = pd.read_csv("movie-pang.csv")
x_train = input_file_df["text"] #used complete data as train data
y_train = input_file_df["class"]
我只用一个特点,sentiment score for each sentence.
我写了这个自定义变压器:
class GetWorldLevelSentiment(BaseEstimator, TransformerMixin):
def __init__(self):
pass
def get_word_level_sentiment(self, word_list):
sentiment_score = 1
for word in word_list:
word_sentiment = swn.senti_synsets(word)
if len(word_sentiment) > 0:
word_sentiment = word_sentiment[0]
else:
continue
if word_sentiment.pos_score() > word_sentiment.neg_score():
word_sentiment_score = word_sentiment.pos_score()
elif word_sentiment.pos_score() < word_sentiment.neg_score():
word_sentiment_score = word_sentiment.neg_score()*(-1)
else:
word_sentiment_score = word_sentiment.pos_score()
print word, " " , word_sentiment_score
if word_sentiment_score != 0:
sentiment_score = sentiment_score * word_sentiment_score
return sentiment_score
def transform(self, review_list, y=None):
sentiment_score_list = list()
for review in review_list:
sentiment_score_list.append(self.get_word_level_sentiment(review.split()))
return np.asarray(sentiment_score_list)
def fit(self, x, y=None):
return self
管道,我用的是:
pipeline = Pipeline([
("word_level_sentiment",GetWorldLevelSentiment()),
("clf", MultinomialNB())])
,然后调用合适的管道:
pipeline.fit(x_train, y_train)
但这是给下面的错误对我说:
This MultinomialNB instance is not fitted yet. Call 'fit' with appropriate arguments before using this method.
是否有人可以指导我什么,我做错了什么?这将是一个很大的帮助。
请张贴错误和完整代码的完整的堆栈跟踪复制的行为。 –
尝试删除这样的括号:(“clf”,MultinomialNB) – CrazyElf
@CrazyElf。删除括号不起作用。管道需要一个实例,而不是类。 –