fossj117 / opinion-mining Goto Github PK

It looks like the prediction models are the unfitted version.

Traceback (most recent call last): File "main.py", line 71, in <module> main() File "main.py", line 55, in main summary = biz.aspect_based_summary() File "/Users/yul0b/Documents/YULU/Workspace/research/ranking/data/opinion-mining-master/classes/business.py", line 93, in aspect_based_summary asp_dict = dict([(aspect, self.aspect_summary(aspect)) for aspect in aspects]) File "/Users/yul0b/Documents/YULU/Workspace/research/ranking/data/opinion-mining-master/classes/business.py", line 184, in aspect_summary prob_opin = Business.OPINION_MODEL.get_opinionated_proba(sent) File "/Users/yul0b/Documents/YULU/Workspace/research/ranking/data/opinion-mining-master/classes/transformers/sentiment.py", line 15, in get_opinionated_proba return OpinionModel.OPINION_MODEL.predict_proba(sent.get_features(asarray=True))[0][1] File "/Library/Python/2.7/site-packages/sklearn/utils/metaestimators.py", line 54, in <lambda> out = lambda *args, **kwargs: self.fn(obj, *args, **kwargs) File "/Library/Python/2.7/site-packages/sklearn/pipeline.py", line 379, in predict_proba Xt = transform.transform(Xt) File "/Library/Python/2.7/site-packages/sklearn/preprocessing/data.py", line 641, in transform check_is_fitted(self, 'scale_') File "/Library/Python/2.7/site-packages/sklearn/utils/validation.py", line 690, in check_is_fitted raise _NotFittedError(msg % {'name': type(estimator).__name__}) sklearn.exceptions.NotFittedError: This StandardScaler instance is not fitted yet. Call 'fit' with appropriate arguments before using this method.