|The classification error Ei of an individual program
i depends on the number of samples incorrectly classified
(false positives plus false
negatives) and is evaluated by the formula:
where f is the number of sample cases incorrectly classified, and
n is the total number of sample cases.
To evaluate the classification error of your model both on the
training and testing data, you just have to go to the Results
Panel after a run.