… Gradient Boosting (XGBoost) algorithm has been followed. The XGBoost algorithm works on
… The results show that feature optimization followed by the XGBoost algorithm gives better …

… can be employed for the task of emotion recognition. XGBoost [15] is an algorithm under the
category of supervised learning. This algorithm runs on both single and distributed systems …

… emotion recognition framework based on physiological signals. To improve the accuracy of
emotion recognition… Among all the machine learning algorithms, gradient boosting tree based …

… Based on the comparative performance analysis of different classifiers in Experiment I, we
selected the XGBoost algorithm as the preferred emotion classifier. The classification results …

… In this paper, we propose a speech emotion recognition framework. It is based on the
XGBoost algorithm for feature selection, and combines the 1D convolutional neural networks and …

… with the XGBoost classifier for the feature ranking and classification, however the performance
can be improved by building the classification models with advanced ML algorithms and …

… accuracy of EEG emotion recognition. In this study, we propose a novel … emotion recognition
algorithm called FCAN–XGBoost, which is a fusion of two algorithms, FCAN and XGBoost. …

… state-of-the-art approaches of emotion recognition. To do this, we applied various feature …
the trained layer of 2DCNN and used XGBoost algorithm for classification. The results that …

… of our proposed emotion recognition algorithm can be … XGBoost models classified with
an accuracy of 88% and 96% respectively. XGBoost outperformed RF in emotion recognition …

… algorithm of four emotional states under continuous audio-visual stimulation in this paper.
XGBoost algorithm … adjustment, strong controllability, and high recognition performance. As a …