We produced a confusion matrix plot as a product of the logistic regression model we trained.
We also generated a 2-D visualization of the data using the two principal components generated by PCA.
Lastly, we selected two most important features from the first principal component and generated a scatterplot. The two features are age and average glucose level.
The plots can be found in stroke/plots folder.
The code can be found in project.py file inside stroke/src/stroke folder.