The true positive rate, the

true negative rate, the false positive rate and the false negative rate was calculated for both the scoring systems and accordingly conclusions were drawn.

NSS had an overall

true negative rate of 55.8%, the false negative rate of 2.1%, true positive rate of 34.4%, and false positive rate of 7.7%.

A total of 6 criteria were used for the assessment of performance, including: true positive rate, false positive rate,

true negative rate, false negative rate, accuracy, and preciseness.

True negative rate ranges were 68.5-91.6 percent, 10.5-92.4 percent, and 81.1-99.9 percent.

Numbers of true positive, false positive, true negative, and false negative pixels were counted within the area scanned by the NubiScope and the true positive rate (TPR; correctly identified clouds) and

true negative rate (TNR; correctly identified cloudless skies) were calculated (cf.

Although Skipfish's SQL detection accuracy was the lowest, it has a false positive rate of 0%, a false negative rate of 23%, and a

true negative rate of 100%.

This discriminative potential can be quantified by the measures of diagnostic accuracy such as true positive rate (sensitivity),

true negative rate (specificity), positive predictive value (PPV), negative predictive value (NPV), likelihood ratio positive (LR+), likelihood ratio negative (LR-), area under the ROC curve, Youden's index, and diagnostic odds ratio (DOR).

Table 2 Contingency table to calculate sensitivity (true positive rate) and specificity (

true negative rate) of HpSA* test in relation to remission of urticaria and dyspepsia after therapy.

Specificity is used to measure the proportion of negatives values which are correctly identified such as the percentage of healthy people who are correctly identified as not having the condition, sometimes called the

true negative rate and the corresponding graph is presented in Fig 7.

There are much evaluation criteria of classifier performance, and the common evaluation criteria are accuracy, true positive rate, false positive rate,

true negative rate, and false negative rate.

The proposed method achieved an average True Positive Rate (TPR) of 94%

True Negative Rate (TNR) of 6% average accuracy of 97% and average error rate of 3%.

Specificity is often referred to as the

true negative rate, and is the calculated fraction of the number of false positives out of the total number of actual negatives.