We have seen output from the ‘confusionMatrix’ command in the ‘caret’ package.
Confusion Matrix and Statistics
Reference
Prediction Female Male
Female 55 24
Male 64 383
Accuracy : 0.8327
95% CI : (0.798, 0.8636)
No Information Rate : 0.7738
P-Value [Acc > NIR] : 0.0005217
Kappa : 0.4576
Mcnemar's Test P-Value : 3.219e-05
Sensitivity : 0.4622
Specificity : 0.9410
Pos Pred Value : 0.6962
Neg Pred Value : 0.8568
Prevalence : 0.2262
Detection Rate : 0.1046
Detection Prevalence : 0.1502
Balanced Accuracy : 0.7016
'Positive' Class : Female
| Female (Actual) | Male (Actual) | |
| Female (Predicted) | 55 (TP) | 24 (FP) |
| Male (Predicted) | 64 (FN) | 383 (TN) |
Accuracy is the proportion of cases where the model correctly predicted the outcome.
(TP + TN) / Total
(55+383)/(55+64+24+383) = 0.8327
Sensitivity is the proportion of females the model correctly predicted.
TP/(TP + FN)
55/(55+64) = 0.4622
Specificity is the proportion of males the model correctly predicted.
TN/(TN + FP)
383/(24+383) = 0.9410
Positive predictive value (PPV)
TP/(TP + FP)
55/(55+24) = 0.6962
Negative predictive value (NPV)
TN/(TN + FN)
383/(383 + 64) = 0.8568
Prevalence is the proportion of females in the total sample set.
(TP + FN) / (TP + FN + FP + TN)
(55+64)/(55+64+24+383) = 0.2262
Detection rate is the proportion of females in total.
TP/(TP + FN + FP + TN)
55/(55+64 + 24+383) = 0.1046
Detection Prevalence is the proportion of predicted females in total.
(TP+FP)/(TP + FN + FP + TN)
(55+24)/(55+64 + 24+383) = 0.1502
Balanced Accuracy is (sensitivity+specificity)/2
(0.4622 + 0.9410)/2 = 0.7016
