Applied Computational Intelligence and Soft Computing / 2018 / Article / Tab 7

Research Article

Performance Assessment of Multiple Classifiers Based on Ensemble Feature Selection Scheme for Sentiment Analysis

Table 7

Comparison of performance of proposed approach with different literature using movie review dataset.

DatasetFeature Selection MethodClassifierPerformance

Pang et al.Internet movie database (IMDb)N-gram featuresSVM 
NB 
ME
82.9 (Accuracy)  
81.5 
81.0

Agarwal et al.Movie (IMDb) 
Product (book, DVD, Electronics)
N-gram, IG,RSAR,   
Hybrid (IG+RSAR)
SVM 
NB
87.7 (F-measure)   
80.9

Al-Moslmi et al.Movie Reviews in the Malay LanguageIG, CHI, Gini IndexSVM 
NB 
KNN
85.33(F-measure)  
80.88 
74.68

Kalaivani et al.Movie (IMDb)  ---------------------SVM 
NB 
KNN
81.71 
72.55 
98.70

Tripathy et al.Movie (IMDb)N-Gram featuresSVM 
ME 
NB 
SGD
88.94 
88.48 
86.23 
85.11

Our ApproachMovie (IMDb)N-gram, Combination of Unigram & bigram with IG, CHI, Gini IndexSVM 
MNB 
KNN 
ME
90.39 (F-measure)  
88.04 
86.03 
87.13

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