Health-Care-Stroke

The data was carefully preprocessed by handling missing values, encoding categorical variables, and addressing class imbalance to improve model performance. Several classification algorithms were trained and evaluated, and performance was measured using metrics such as accuracy, precision, recall, F1-score, and confusion matrix.