Computer Science ›› 2016, Vol. 43 ›› Issue (10): 206-210.doi: 10.11896/j.issn.1002-137X.2016.10.039

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TSF Feature Selection Method for Imbalanced Text Sentiment Classification

WANG Jie, LI De-yu and WANG Su-ge   

  • Online:2018-12-01 Published:2018-12-01

Abstract: In the imbalanced datasets,the imbalanced distribution of the samples is often accompanied by the imbalanced distribution of features.The features,which often appear in the majority class,rarely appear in the minority class.According to the characteristics of the imbalanced feature distribution,we proposed a new two-side fisher (TSF) feature selection method.TSF can control combination of positive features and negative features explicitly and tackle the imba-lanced problem in the level of feature.Experiments are conducted on the book reviews and COAE2014 imbalanced dataset.Experimental results indicate that TSF is an effective feature selection method for the imbalanced problem.

Key words: Imbalanced,Text sentiment classification,Positive and negative feature,Two-side feature selection

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