Table of Contents

About Dataset:

• Age : Age of the patient

• Sex : Sex of the patient

• exang: exercise induced angina (1 = yes; 0 = no)

• ca: number of major vessels (0-3)

• cp : Chest Pain type chest pain typ

  • Value 1: typical angina
  • Value 2: atypical angina
  • Value 3: non-anginal pain
  • Value 4: asymptomatic

• trestbps : resting blood pressure (in mm Hg)

• chol : cholestoral in mg/dl fetched via BMI sensor

• fbs : (fasting blood sugar > 120 mg/dl) (1 = true; 0 = false)

• rest_ecg : resting electrocardiographic results

  • Value 0: normal
  • Value 1: having ST-T wave abnormality (T wave inversions and/or ST elevation or depression of > 0.05 mV)
  • Value 2: showing probable or definite left ventricular hypertrophy by Estes’ criteria

• thalach : maximum heart rate achieved

• target : 0= less chance of heart attack 1= more chance of heart attack

Procedures

• Data preparation was done thoroughly.
• Did Hyper parameter tunning using GridSearchCV
• Among GaussianNB, AdaBoostClassifier, DecisionTreeClassifier, KNeighborsClassifier, XGBoost, SVM, RandomForest, LogisticRegression, RandomForest performed best with score of 86%

Link to github repo