Performance evaluation of hybrid feature selection technique for sentiment classification based on food reviews

• Main Authors: Awang, Suryanti, Mohd Nafis, Nur Syafiqah
• Format: Conference or Workshop Item
• Language: English; English
• Published: IEEE 2021
• Subjects: Q Science (General); QA76 Computer software
• Online Access: http://umpir.ump.edu.my/id/eprint/33473/1/Performance%20evaluation%20of%20hybrid%20feature%20selection%20technique_FULL.pdf; http://umpir.ump.edu.my/id/eprint/33473/2/Performance%20evaluation%20of%20hybrid%20feature%20selection%20technique.pdf; http://umpir.ump.edu.my/id/eprint/33473/; https://doi.org/10.1109/ICSECS52883.2021.00038

This paper presents an evaluation of the performance efficiency of sentiment classification using a hybrid feature selection technique. This technique is able to overcome the issue of lack in evaluating features importance by using a combination of TF-IDF+SVM-RFE (Term Frequency-Inverse Document Fre...