transactionattributes, that is, asset specificity, transaction frequency, and uncertainty. The research is based on the theoretical …

lead to improved treatment and thus reduce medical mistakes. The sensitivity and specificity are two important measurements … confidence interval for the sensitivity at a fixed level of specificity for the test. In this thesis, we propose three empirical …

of sensitivity and specificity for all the possible values of the cut-point. This dissertation concentrates on …

Sensitivity and specificity are common measures of the accuracy of a diagnostic test. The usual estimators of these … and specificity based on this subset of subjects are typically biased; this is known as verification bias. In this … connecting the (sensitivity, 1? specificity) points at each cutpoint of the test using step functions and/or line segments. This …

and specificity values from these data for different scoring systems. The interest of our approach was illustrated in a …

This report introduces a novel approach to performing inference and learning in Dynamic Bayesian Networks (DBN). The … traditional approach to inference and learning in DBNs involves conditioning on one or more finite-length observation sequences … solving inference problems (i.e., computing P(X|Φ)) and learning problems (i.e., computing P(Θ|Φ)) using techniques from the …