/Heart_Disease

Machine Learning

Primary LanguageJupyter Notebook

Heart_Disease

  • Table Of Content:

  • DataSet Link
  • Details
  • Score on Diff. Model

Heart


Heart


  • age: The person's age in years
  • sex: The person's sex (1 = male, 0 = female)
  • cp: The chest pain experienced (Value 1: typical angina, Value 2: atypical angina, Value 3: non-anginal pain, Value 4: asymptomatic)
  • trestbps: The person's resting blood pressure (mm Hg on admission to the hospital)
  • chol: The person's cholesterol measurement in mg/dl
  • fbs: The person's fasting blood sugar (> 120 mg/dl, 1 = true; 0 = false)
  • restecg: Resting electrocardiographic measurement (0 = normal, 1 = having ST-T wave abnormality, 2 = showing probable or definite left ventricular hypertrophy by Estes' criteria)
  • thalach: The person's maximum heart rate achieved
  • exang: Exercise induced angina (1 = yes; 0 = no)
  • oldpeak: ST depression induced by exercise relative to rest ('ST' relates to positions on the ECG plot. See more here)
  • slope: the slope of the peak exercise ST segment (Value 1: upsloping, Value 2: flat, Value 3: downsloping)
  • ca: The number of major vessels (0-3)
  • thal: A blood disorder called thalassemia (3 = normal; 6 = fixed defect; 7 = reversable defect)
  • target: Heart disease (0 = no, 1 = yes)

  • Applying simple model without hypertuning

  • KNN - 0.8448387096774195
  • RandomForestClassifier = 0.8248387096774193
  • DecisionTreeClassifier = 0.7353763440860214