Heart-Disease-Analysis-in-R 🩺❤

About :

1. Libraries
2. Data Transformation
3. Data Visualization
4. Correlation
5. Training and testing the data
6. Support vector machine
7. Random forest
8. Comparison of AUC and Accuracy between models
9. Confusion matrix

Result :

📍 A comparison of the area under the ROC and the accuracy of the model predictions shows that logistic regression performs best (accuracy of 0.87). Tree-based methods shows low accuracy.

📍 Random forest has higher accuracy than support vector machine to detect heart disease.

Languages used:

📣 Feel free to have a look at this repository !🤗

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