Figure 6.
The image presents a flowchart outlining the process for analysing laboratory test data. The first box denotes the collection of laboratory test data, indicating that one hundred and twenty-one tests were performed on treated expansive soils. Below this, the next section displays input and output parameters labelled as R 1, R 2, R 3, R 4, R 5, R 6, and R 7. The third box lists various machine learning algorithms or models, specifically noting Random Forest, Artificial Neural Network, Support Vector Machine, and Gaussian Process Regression. The final section presents the performance measures for these models, which include R-squared, Mean Absolute Error, Root Mean Squared Error, Relative Absolute Error, and Relative Root Squared Error. Dashed red lines separate each section, and the flow of information proceeds left to right through the boxes, indicating a step-by-step process.The flowchart used to anticipate CBR values using a data-driven method