The x axis of the ROC plot represents the false-positive error rate, which is equal to 1 minus the model specificity, where the model specificity is the class prediction accuracy of nonignitions.
The class prediction accuracy of fire ignitions is also known as the model sensitivity or the true-positive rate (TPR), while the class prediction of nonignitions is also known as the model specificity or the true-negative rate (TNR).
Model specificity emerges from the DBS, so that model execution is carried out by the statecharts executing with the aid of specific data extracted from the DBS dynamically.
However, some TGFβ-related proteins exhibited model specificity implying that the TGFβ response is tailored to each condition.
Meanwhile, when we combined the variables of SNAP, gestational age, apnea of prematurity, PDA, and surfactant use in the final model, specificity increased to 90%, and positive likelihood ratio increased to 7.4.
For the male classification model, the specificity was 90.3% and the bootstrapped sensitivity was 51.0%.
For the female classification model, the specificity was 90.0% and the sensitivity was 37.1%.
The only significant difference was for NTproBNP ≤300ng/L; when adding prevalence differences into the model the specificity was significantly higher at 0.93 (95% confidence interval 0.84 to 0.97, P<0.01).
Therefore, it is neccessary to investigate multivariate and feature-selective methods to model the specificity and to extract rules from the model.
This allows us to train complex models of specificity without the risk of overfitting the training data.
