This project containts End-to-End Heart Disease Classification Project.

• In this project, I first perform some exploratory data analysis on the dataset to identify patterns by comparing various features within the data. To establish a baseline model,

• I then compare/ build three different machine learning models (Logistic Regression, K-nearest Neighbours classifier and Random Forest Classifier) from Scikit-Learn.

• Then I performed Hyperparameter tuning:

  • first by hand (with loops),
  • then with RandomizedSearchCV,
  • GridSearchCV

• I also use 5-fold cross-validation.

• Evaluation is performed using:

  • Accuracy
  • ROC curve & AUC score
  • Confusion matrix
  • Classification report
  • Precision
  • Recall
  • F1-score