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An ensemble pattern classification system based on multi tree genetic programming for improving intension pattern recognition using brain computer interaction

Title
An ensemble pattern classification system based on multi tree genetic programming for improving intension pattern recognition using brain computer interaction
Authors
Lee, Jong-HyunAn, JinungAhn, Chang Wook
DGIST Authors
An, Jinung
Issue Date
2014
Citation
Communications in Computer and Information Science, 472, 239-246
Type
Article
Article Type
Article
Keywords
Brain Computer InteractionBrain Computer InteractionsClassificationClassification (of Information)Classification AccuracyClassification SystemComputation TheoryComputer ProgrammingComputer Systems ProgrammingEnsemble ClassificationEnsemble ClassifierEnsemble ClassifiersEnsemble LearningGenetic AlgorithmsGenetic ProgrammingIntension Pattern RecognitionMulti-TreesMultitreeParallel LearningPattern RecognitionPattern Recognition SystemsProgramming Mechanism
ISSN
1865-0929
Abstract
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.
URI
http://hdl.handle.net/20.500.11750/2136
Publisher
Springer Verlag
Related Researcher
Files:
There are no files associated with this item.
Collection:
Convergence Research Center for Wellness1. Journal Articles


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