Sentence examples for roc metric from inspiring English sources

For performance evaluation, sensitivity, specificity, accuracy, and the area under the receiver operator curve (ROC) metric are used.

Also weighting each active based on the size of the lead series to which it belongs [6] or incorporating the notion of early recognition into the ROC metric formalism [7] can give useful information about the enrichment of the active molecules.

The ROC metric measures the area under the ROC curve.

For evaluating the performance of different combinations of protein conformers, we considered: the Area Under the Accumulation Curve (AUAC), the area under the Receiver Operating Characteristic curve (ROC), the Enrichment Factor (EF) [45] at different thresholds, the Robust Initial Enhancement (RIE) [46], and the Boltzmann-Enhanced Discrimination of ROC metric (BEDROC) [5].

The ROC metric from Python scikit-learn [ 38] was used to construct ROC curves and calculate associated AUC values.

The performance of these predictions was assessed using the area under the receiver operating curve (AUC-ROC), a metric that quantifies the ability of a method to predict positive examples which, in our case, is phase specific expression.

As a summary metric for ROC, the area under the ROC curve (AUC), as its name indicates, measures the average accuracy of the prediction.

ROC can be measured as a single metric by calculating the area under the ROC curve (AUC).

The hill-climbing algorithm uses the 10-fold cross-validation area under the ROC curve as the metric to optimize.

The second employed early enrichment metric, the ROC enrichment (ROCE), measures the performance at a predefined false positive rate or top fraction of true decoys.

The ROC curve serves as one metric for evaluating a diagnostic in that it provides a quantitative measure of the ability of the test to distinguish between unaffected and affected individuals.