A multiobjective weighted voting ensemble classifier based on differential evolution algorithm for text sentiment classification
作者：
Highlights：
• A novel multi-objective differential evolution algorithm based classifier ensemble for text sentiment classification.
• An empirical comparison of weighted and unweighted voting schemes.
• Extensive empirical analysis on metaheuristic based voting schemes for sentiment analysis.
• High classification accuracies for text sentiment classification (98.86% for Laptop dataset).
摘要
• A novel multi-objective differential evolution algorithm based classifier ensemble for text sentiment classification.• An empirical comparison of weighted and unweighted voting schemes.• Extensive empirical analysis on metaheuristic based voting schemes for sentiment analysis.• High classification accuracies for text sentiment classification (98.86% for Laptop dataset).
论文关键词：Sentiment analysis,Ensemble learning,Weighted majority voting,Multiobjective optimization
论文评审过程：Received 7 December 2015, Revised 10 May 2016, Accepted 3 June 2016, Available online 7 June 2016, Version of Record 14 June 2016.
论文官网地址：https://doi.org/10.1016/j.eswa.2016.06.005
