Logistic Regression
- Precision: 0.10
- Recall: 0.85
- F1 Score: 0.63
Confusion Matrix
The confusion matrix demonstrates how the test data performed against the logistic regression machine learning model. Our results demonstrated that we have 53 true positives (TP), 9 false negatives (FN), 470 false positives (FP), and 746 true negative (TN). Our goal was to aim for a greater recall and have a relatively low number for the false negatives as these results can potentially be fatal since we would be telling the user they are not at risk of having a stroke when they are. Our logistic regression model had a 0.85 recall and 9 false negatives.