Figure 11
From: Sea level variability and modeling in the Gulf of Guinea using supervised machine learning
The architecture of the Random Forest Regression (RFR) Model. The architecture has three decision trees as estimators in the random forest ensemble. Each decision tree operates independently, with the depth varying based on the data and problem complexity. The input data contains three features, which are used to train and construct the three decision trees. The RFR model effectively aggregates the predictions of these decision trees to make robust and accurate regression predictions.
