This project containts End-to-End Heart Disease Classification Project.
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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,
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I then compare/ build three different machine learning models (Logistic Regression, K-nearest Neighbours classifier and Random Forest Classifier) from Scikit-Learn.
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Then I performed Hyperparameter tuning:
- first by hand (with loops),
- then with RandomizedSearchCV,
- GridSearchCV
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I also use 5-fold cross-validation.
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Evaluation is performed using:
- Accuracy
- ROC curve & AUC score
- Confusion matrix
- Classification report
- Precision
- Recall
- F1-score