def create_union_model(params=None):
def preprocessor(tweet):
tweet = tweet.lower()
for k in emo_repl_order:
tweet = tweet.replace(k, emo_repl[k])
for r, repl in re_repl.iteritems():
tweet = re.sub(r, repl, tweet)
return tweet.replace("-", " ").replace("_", " ")
tfidf_ngrams = TfidfVectorizer(preprocessor=preprocessor,
analyzer="word")
ling_stats = LinguisticVectorizer()
all_features = FeatureUnion(
[('ling', ling_stats), ('tfidf', tfidf_ngrams)])
#all_features = FeatureUnion([('tfidf', tfidf_ngrams)])
#all_features = FeatureUnion([('ling', ling_stats)])
clf = MultinomialNB()
pipeline = Pipeline([('all', all_features), ('clf', clf)])
if params:
pipeline.set_params(**params)
return pipeline
04_sent.py 文件源码
python
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