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.
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.
EvanDietrich/Heart-Failure-Prediction-Classifer-Comparison
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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.
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