15759879600/South-African-Heart-Disease-Data-Analysis-and-Modeling

# South-African-Heart-Disease-Data-Analysis-and-Modeling 1. Conducted data preprocessing, feature engineering, and visualization to explore relationships between variables. 2. Applied analysis of variance to identify key risk factors influencing heart disease prediction. 3. Built and optimized models using Random Forest, SVM, XGBoost, and KNN, selecting SVM as the best model based on accuracy, F1-score, and ROC AUC. 4. The final model effectively identifies high-risk individuals, offering a reliable tool for early heart disease screening.