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An ensemble pattern classification system based on multi tree genetic programming for improving intension pattern recognition using brain computer interaction
- An ensemble pattern classification system based on multi tree genetic programming for improving intension pattern recognition using brain computer interaction
- Lee, Jong-Hyun; An, Jin Ung; Ahn, Chang Wook
- DGIST Authors
- An, Jin Ung
- Issue Date
- Communications in Computer and Information Science, 472, 239-246
- Article Type
- Brain Computer Interaction; Brain Computer Interactions; Classification; Classification (of Information); Classification Accuracy; Classification System; Computation Theory; Computer Programming; Computer Systems Programming; Ensemble Classification; Ensemble Classifier; Ensemble Classifiers; Ensemble Learning; Genetic Algorithms; Genetic Programming; Intension Pattern Recognition; Multi-Trees; Multitree; Parallel Learning; Pattern Recognition; Pattern Recognition Systems; Programming Mechanism
- Ensemble learning is one of the successful methods to construct a classification system. Many researchers have been interested in the method for improving the classification accuracy. In this paper, we proposed an ensemble classification system based on multitree genetic programming for intension pattern recognition using BCI. The multitree genetic programming mechanism is designed to increase the diversity of each ensemble classifier. Also, the proposed system uses an evaluation method based on boosting and performs the parallel learning and the interaction by multitree. Finally, the system is validated by the comparison experiments with existing algorithms. © Springer-Verlag Berlin Heidelberg 2014.
- Springer Verlag
- Related Researcher
Brain Robot Interaction Lab
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