Fig. 5: Schematic representation of the 100-fold cross-validation training process of the Random Forest algorithm.
From: Machine learning assisted real-time acoustic monitoring of laser cleaning in Heritage conservation
After optimizing the hyperparameters of the model, we conclude with a model that features 100 estimators (decision trees), a maximum depth of 12 for each tree, and a minimum number of samples per leaf of 10.
