计算机科学 ›› 2013, Vol. 40 ›› Issue (1): 200-202.

• 人工智能 • 上一篇    下一篇

随机森林算法在肌电的重要特征选择中的应用

张洪强,刘光远,赖祥伟   

  1. (西南大学电子信息工程学院 重庆400715) (西南大学计算机与信息科学学院 重庆400715)
  • 出版日期:2018-11-16 发布日期:2018-11-16

Application of Random Forest Algorithm in Improtant Feature Selection from EMG Signal

  • Online:2018-11-16 Published:2018-11-16

摘要: 在肌电信号的情感识别问题中,如何从高维特征中找出起关键作用的特征,一直是情感识别的难题。使用随机森林算法,并依照其对特征的评价准则,来计算肌电信号的126个初始特征在不同情感模式分类中的贡献度。依照每个特征的重要程度,优先组合贡献度大的特征并将其用于情感的分类。实验数据验证了该方法的有效性。

关键词: 情感识别,随机森林,肌电信号,特征选择

Abstract: It is a hard problem that how to find the effective feature from high-dimensional feature in EMU signal emotion recognition. I}his paper used random forest algorithm to comput the contribution in different emotion recognition of the 126 EMU signal, depending on the feature evaluation criteria of random forest algorithm, and then preferentially made up the features that have more contribution to emotion recognition,and used then to emotion recognition. Experiments show it is reasonable.

Key words: Emotion recognition, Random forest, EMG signal, Feature selection

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