Figure 2:

This figure shows the machine learning pipeline used to predict each personality trait. The pipeline includes nested cross-validation with two loops. The outer loop is leave-one-participant out cross-validation for evaluating models’ performance, and the inner loop is a grid search cross-validation used for tuning hyper-parameter. The figure provides the whole structure of the leave-one-participant-out cross-validation and a case of grid search cross-validation of an iteration i for the outer loop.