dadouchanet/machine_learning_predicting_heart_disease

Predicting male population heart-disease in South Africa with machine learning # machine_learning_predicting_heart_disease Predicting male population heart-disease in South Africa with machine learning ## The dataset : SAheart.txt : n = 462 sample of males in a heart-disease high-risk in the region of the Western Cape, South Africa Aim of the work : predict the value of the “chd” (coronary heart disease) response variable The parameters : p = 9 - sbp : systolic blood pressure - tobacco : cumulative tobacco - ldl : low densiity lipoprotein cholesterol - adiposity - famhist : family history of heart disease - typea : type-A behavior - obesity - alcohol : current alcohol consumption - age : age at onset ## 5 different models : We try 5 machine learning models in order to compare the models between them and to choose the best predicting model : - Decision Tree model - Bagging model - Random Forest model - AdaBoost model - Gradient Boosting model We fit the 5 models and make predictions