Proposed version:
editLet us define an experiment from P positive instances and N negative instances for some condition. The four outcomes can be formulated in a 2×2 contingency table or confusion matrix, as follows:
The relationships of related formulas to the information in the confusion matrix. can be viewed as follows:
True condition | ||||
Condition positive | Condition negative | |||
Predicted condition |
Predicted condition positive |
True positive Related formulas: Accuracy, Precision/Positive Predictive Value (PPV), Prevalence, True Positive Rate (TPR)/Sensitivity/Recall, False Discovery Rate (FDR), False Negative Rate (FNR)/Miss Rate, F1 Score, Positive Likelihood Ratio (LR+), Negative Likelihood Ratio (LR-) |
False positive (Type I error) Related formulas: Precision/Positive Predictive Value (PPV), Specificity/True Negative Rate (TNR), False Positive Rate (FPR)/Fall-out, False Discovery Rate (FDR), F1 Score, False Omission Rate (FOR), Positive Likelihood Ratio (LR+), Negative Likelihood Ratio (LR-) |
|
Predicted condition negative |
False negative (Type II error) Related formulas: Prevalence, True Positive Rate (TPR)/Sensitivity/Recall, Negative Predictive Value (NPV), False Negative Rate (FNR)/Miss Rate, False Omission Rate (FOR), F1 Score, Negative Likelihood Ratio (LR-) |
True negative Related formulas: Accuracy, Precision (PPV), Specificity/True Negative Rate (TNR), Negative Predictive Value (NPV), False Positive Rate (FPR)/Fall-out, False Omission Rate (FOR), Positive Likelihood Ratio (LR+), Negative Likelihood Ratio (LR-) |