True Class | Predicated Class |
|---|
YES | NO |
|---|
YES | True Positive (TP) | False Negative (FN) |
NO | False Positive (FP) | True Negative (TN) |
- Note: TP: The number of samples correctly predicted as positive (e.g., disease present) by the model. This reflects the model's ability to identify true disease patients. FP: The number of samples falsely predicted as positive (disease present) by the model, when they are actually negative. This may lead to unnecessary medical interventions or patient anxiety. FN: The number of samples falsely predicted as negative (disease absent) by the model, when they are actually positive. This may result in missed diagnoses, posing a serious threat to patients' health.TN: The number of samples correctly predicted as negative (disease absent) by the model. This demonstrates the model's accuracy in excluding healthy individuals
