Lavanya Al

Feature Correlation and Class Balancing Effects on Random Forest Accuracy in Diabetes Risk Prediction Using the Teboul Health Indicators Dataset

A Random Forest-based predictive framework for diabetes risk assessment using the Teboul Health Indicators Dataset is presented, indicating that appropriate class balancing improves sensitivity and fairness in diabetes classification, while Random Forest provides model interpretability through feature-importance analys...