Evaluating your decision tree performance
This section explains how to evaluate the results of your decision tree.
Below is a confusion matrix using the data from your test Job.
The model tries to predict (conversion = no) as being either true of false.
- TN = 15
- TP = 446
- FN = 12
- FP = 41
- Accuracy = (TP+TN)/Total = (15+446)/(446+15+12+41) = .90
- Sensitivity = TP/(TP+FN) = (446)/(446+12) = .97
- Specificity = TN/(TN+FP) = (15)/(15+41) = .27
When you tested the tree model:
- It was correct 90% of the time (accuracy)
- It accurately predicted 97% of those persons who did not result in a conversion (sensitivity)
- It accurately predicted 27% of those persons who did result in a conversion (specificity)