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Fig. 1 | Brain Informatics

Fig. 1

From: Enhancing biofeedback-driven self-guided virtual reality exposure therapy through arousal detection from multimodal data using machine learning

Fig. 1

Figures show the performance (accuracy, precision, recall and F1-Score) of the publicly available data set that we used to train our model. Here, we consider QDA, GNB, SVM, MLP, ADB, KNN, DT and RF ML models. KNN, DT and RF have been used with multiple parameter settings. The figure on the top shows the performance of the SWELL [80] data set and the figure on the bottom shows the performance on the EEG data set of [79]

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