machine-learning-healthcare

Feature selection and predictive accuracy across clinical dataset. Classifier models used: Logistic Regression, K Nearest Neighbours, Support Vector Machine, Decision Tree, Random Forest, Neural Network, XGBoost. 95.0% predictive accuracy w/ Decision Tree Model.