Table 2 Classification outcomes
From: A review of epileptic seizure detection using machine learning classifiers
Acronym | Detection type | Real-world scenario |
|---|---|---|
TP | True-positive | If a person suffers to ‘seizure’ and also correctly detected as a ‘seizure’ |
TN | True-negative | The person is actually normal and the classifier also detected as a ‘non-seizure’ |
FP | False-positive | Incorrect detection, when the classifier detects the normal patient as a ‘seizure’ case |
FN | False-negative | Incorrect detection, when the classifier detects the person with ‘seizure(s)’ as a normal person. This is a severe problem in health informatics research |