Table 1.

Pseudocode.

Algorithm Steps
1. Initialize dataset
2. Conduct exploratory data analysis
2.1. Use descriptive statistics, box plots, pair plots, and clustering techniques
3. Preprocess data
3.1. Scale numerical variables with StandardScaler
4. Build Machine Learning models
4.1. For each model (Logistic Regression, Decision Tree, Random Forest, Support Vector Machines)
4.1.1. Apply GridSearchCV for parameter tuning
4.1.2. Train model on training data
4.1.3. Evaluate model on validation data
5. Determine the most significant predictors
6. Validate research hypothesis