Fig. 3: Predictive modeling for AWE-S ratings with behavioral metrics.
From: Awe is characterized as an ambivalent affect in the human behavior and cortex
a beta coefficients of each behavioral metric in the linear mixed effect models. Error bars denote 95% confidence intervals of fixed effects’ estimates. Purple bars show the estimates of ambivalence-related features. Bolded statistics indicate statistically significant results at P < 0.05. b predictive performances of AutoML-based best model (GBM) and linear ridge regression model (GLM). c variable importance value of behavioral metrics in the GBM-based prediction. Importance value was scaled from 0 to 1 by the value of duration of ambivalent feelings. Purple bars show the importance of ambivalence-related features. d shapley values of behavioral metrics in the GBM-based prediction. Results are based on 43 participants’ self-reports for all VR clips.
