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Performance of the models was measured using precision and recall after application of the various class-specific binary thresholds (previously calculated) for each target.
Hazard ratios (HR) together with 95% confidence intervals (CI) were estimated, and the performance assessment of the different survival models was measured using the concordance index (C-index).
The calibration of the models was measured using calibration curves [ 39].
Performance of the models was measured using an R2 value, Clarke error grids (CEG) and rate-error grid analysis (R-EGA).
The discriminant performance of models was measured using the time-dependent area under the curve (AUC) using the SurvivalROC R package 32.
The discriminate ability of the three models was measured using discrimination metrics including sensitivity, specificity, Youden index, positive predictive value (PPV), negative predictive value (NPV), Brier score and AUC values (Table 3).
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The wind pressure on various surfaces of the building models are measured using the Baratron pressure gauge from MKS Corporation Ltd.
The performances of the models were measured using area under the receiver operating characteristic curve (AUC) [ 40], which is frequently used to evaluate prediction models in the biomedical informatics field [ 41].
An electrochemical model for lithium polymer cells was developed and a parameter set for the model was measured using a series of laboratory experiments.
The quality of each network and regression model was measured using coefficients of determination, relative approximation errors (RAE), and root mean square errors (RMS).
Wind load acting on the container crane model was measured using a seven-component balance with varying wind direction (yaw angle) in two different ABLs.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com