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首页> 外文期刊>International journal of cognitive informatics and natural intelligence >A Novel Emotion Recognition Method Based on Ensemble Learning and Rough Set Theory
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A Novel Emotion Recognition Method Based on Ensemble Learning and Rough Set Theory

机译:基于集成学习和粗糙集理论的情绪识别新方法

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摘要

Emotion recognition is a very hot topic, which is related with computer science, psychology, artificial intel ligence, 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.
机译:情感识别是一个非常热门的话题,与计算机科学,心理学,人工智慧等相关。它总是通过经典方法(如ANN,模糊集,SVM,HMM等)对面部或音频信息进行处理。集成学习理论是机器学习的一种新颖方法,集成方法被证明是一种有效的模式识别方法。本文提出了一种基于选择性集成特征选择和粗糙集理论的集成学习方法。该方法可以满足基本分类器的准确性和多样性之间的折衷。此外,该方法被认为是一种情感识别方法,并通过仿真实验证明是有效的。

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