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(IFS)' and 'GA Feature Selection(GAFS)'. Afterwards, the results (selected features) of the IFS and GAFS were applied to an emotion recognition system (ERS), which was also implemented in this research. Especially, our interactive feature selection method was based on a Reinforcement Learning Algorithm since it required responses from human users. By performing the IFS, we were able to obtain three top features and apply them to the ERS. We compared those results from a random selection and Sequential Forward Selection (SFS) and Genetic Algorithm Feature Selection (GAFS). © Springer-Verlag Berlin Heidelberg 2007.
CITATION STYLE
Sim, K. B., Jang, I. H., & Park, C. H. (2007). The development of interactive feature selection and GA feature selection method for emotion recognition. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4694 LNAI, pp. 73–81). Springer Verlag. https://doi.org/10.1007/978-3-540-74829-8_10
Mendeley helps you to discover research relevant for your work.