International Journal of Man-Machine Studies
Boosting a weak learning algorithm by majority
Information and Computation
Machine Learning
Affective computing
The Random Subspace Method for Constructing Decision Forests
IEEE Transactions on Pattern Analysis and Machine Intelligence
Feature selection for ensembles
AAAI '99/IAAI '99 Proceedings of the sixteenth national conference on Artificial intelligence and the eleventh Innovative applications of artificial intelligence conference innovative applications of artificial intelligence
Toward Machine Emotional Intelligence: Analysis of Affective Physiological State
IEEE Transactions on Pattern Analysis and Machine Intelligence - Graph Algorithms and Computer Vision
Using Rough Sets with Heuristics for Feature Selection
Journal of Intelligent Information Systems
Machine Learning
Ensembling neural networks: many could be better than all
Artificial Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Pattern Recognition Letters - Special issue: Rough sets, pattern recognition and data mining
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
Ensemble Methods in Machine Learning
MCS '00 Proceedings of the First International Workshop on Multiple Classifier Systems
Affective computing: challenges
International Journal of Human-Computer Studies - Application of affective computing in humanComputer interaction
Solving multiclass learning problems via error-correcting output codes
Journal of Artificial Intelligence Research
An approach for selective ensemble feature selection based on rough set theory
RSKT'07 Proceedings of the 2nd international conference on Rough sets and knowledge technology
Editorial Recent Advances in Cognitive Informatics
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Ensembles of Classifiers Based on Approximate Reducts
Fundamenta Informaticae - Concurrency Specification and Programming (CS&P'2000)
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Emotion recognition is a very hot topic, which is related with computer science, psychology, artificial intelligence, etc. It is always performed on facial or audio information with classical method such as ANN, fuzzy set, SVM, HMM, etc. Ensemble learning theory is a novelty in machine learning and ensemble method is proved an effective pattern recognition method. In this paper, a novel ensemble learning method is proposed, which is based on selective ensemble feature selection and rough set theory. This method can meet the tradeoff between accuracy and diversity of base classifiers. Moreover, the proposed method is taken as an emotion recognition method and proved to be effective according to the simulation experiments.