Figure 7.
The image depicts a scatter plot illustrating the relationship between predicted and measured California Bearing Ratio (C B R) percentages, with the horizontal axis representing measured C B R percentages ranging from five to fifty percent, and the vertical axis showing predicted C B R percentages within the same range. Data points plotted correspond to predictions from four different algorithms: Support Vector Machine (S V M), Gaussian Process Regression (G P R), Artificial Neural Networks (A N N), and Random Forest (R F). A dotted linear fit line demonstrates the overall trend in the data. Included is a small inset graph showing a close-up view of the predictions for a specific range, with all algorithms clearly marked. Additionally, a table within the image presents the R-Squared values for each algorithm, indicating their statistical performance in predictions.Comparison between measured and predicted CBR values for model training