Confusion matrix interpretation
You are given the actual diagnoses and predicted diagnoses for the heart_disease dataset - actuals
and predictions
respectively. Import and create a confusion matrix of these diagnoses using the imported confusion_matrix()
function in order to select the correct answer. Note that the sklearn output format for confusion matricies is:
Actual: Heart disease | Actual: No heart disease | |
---|---|---|
Predicted: Heart disease | ||
Predicted: No heart disease |
⚠️ Note: Type your code in the IPython Shell terminal and press Enter.
This exercise is part of the course
End-to-End Machine Learning
Hands-on interactive exercise
Turn theory into action with one of our interactive exercises
