Optimal feature selection for learning-based algorithms for sentiment classification

• Main Authors: WANG, Zhaoxia, LIN, Zhiping
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2020
• Subjects: Machine learning; feature selection; Optimal feature selection; relationship analysis; sentiment classification; social media; text analysis; Computational Engineering; Databases and Information Systems; Theory and Algorithms
• Online Access: https://ink.library.smu.edu.sg/sis_research/5887; https://ink.library.smu.edu.sg/context/sis_research/article/6882/viewcontent/Wang_Lin2020_Article_OptimalFeatureSelectionForLear__1_.pdf
• Institution: Singapore Management University

Sentiment classification is an important branch of cognitive computation—thus the further studies of properties of sentiment analysis is important. Sentiment classification on text data has been an active topic for the last two decades and learning-based methods are very popular and widely used in v...