Algorithm 2: Support Vector Machine (SVM) algorithm pseudocode

Input:

- Training data: X_train, y_train

- Testing data: X_test

- Kernel function: K

- Regularization parameter: C

- Class weighting: w

Output: Predicted macrosomia risk for each test

Train SVM:

Compute K_train and W_train

Solve optimization problem to obtain α and b

Predict macrosomia risk:

Compute K_test

Compute predicted risk using α, b, and K_test

Return predicted risk for each test