Abstract
This paper presents an original feature selection method for Emotion Recognition which includes many original elements. Feature selection has some merit regarding pattern recognition performance. Thus, we developed a method called an ‘Interactive Feature Selection’ and the results (selected features) of the IFS were applied to an emotion recognition system (ERS), which was also implemented in this research. Our innovative feature selection method was based on a Reinforcement Learning Algorithm and since it required responses from human users, it was denoted an ‘Interactive Feature Selection’. By performing an IFS, we were able to obtain three top features and apply them to the ERS. Comparing those results from a random selection and Sequential Forward Selection(SFS) and Genetic Algorithm Feature Selection(GAFS), we verified that the top three features were better than the randomly selected feature set.
This research was supported by the brain Neuroinformatics research Program by Ministry of Commerce,Industry and Energy.
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Park, CH., Sim, KB. (2006). The Novel Feature Selection Method Based on Emotion Recognition System. In: Huang, DS., Li, K., Irwin, G.W. (eds) Computational Intelligence and Bioinformatics. ICIC 2006. Lecture Notes in Computer Science(), vol 4115. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11816102_77
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DOI: https://doi.org/10.1007/11816102_77
Publisher Name: Springer, Berlin, Heidelberg
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