随机森林算法在肌电的重要特征选择中的应用

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

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。

It is a hard problem that how to find the effective feature from high-dimensional feature in EMG signal emotion recognition.This paper used random forest algorithm to comput the contribution in different emotion recognition of the 126 EMG 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.