The multilayer sentiment analysis model based on Random forest

With the rapid development of the Internet, artificial intelligence has gain widespread concern. Under the background, as one closely related discipline sentiment analysis's relevant research work have also been expanded. First, the paper analy existing text sentiment analysis method, compare the effect of a variety of emotional classification trained by traditional machine learning model. Second, it introduce ensemble learning methods, use random forest as meta learning method train base classifiers which trained through different feature sets. Though the experiments concluded that: by using a different set of features and different base classifiers, the ensemble model can obtain significant promotion, so the paper propose a new model "MFMB-ME, Multi-Features Multi-Base-Classifiers Meta Ensemble Learning Sentiment Analysis Model".