stats
confusion matrix (classifiers, diagnostic tests):
| Actually positive | Actually negative | |
|---|---|---|
| Predicted positive | True positive (TP) | False positive (FP) |
| Predicted negative | False negative (FN) | True negative (TN) |
- Accuracy
- How often was the prediction correct overall?
(TP + TN) / (TP + TN + FP + FN)- Precision / Positive Predictive Value (PPV)
- Of the positive predictions, how many were right?
TP / (TP + FP)- Negative Predictive Value (NPV)
- Of the negative predictions, how many were right?
TN / (TN + FN)- True positive rate (Recall / Sensitivity / Hit rate / Power)
- Of the actual positives, how many did we find?
TP / (TP + FN)- True negative rate (Specificity)
- Of the actual negatives, how many did we reject correctly?
TN / (TN + FP)- False positive rate (Fall-out)
FP / (FP + TN)- False negative rate (Miss rate)
FN / (FN + TP)