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Each classifier for a TF is evaluated using a leave-one-out cross-validation (LOOCV) approach, and the reported performance measures (accuracy, and positive predictive value) are the average measurements over all 50 classifiers.
To estimate the overall performance of the MLPNN model, statistical measures (accuracy, specificity, sensitivity) were averaged.
The measures Accuracy, F-recall, and M-recall are defined as follows.
To estimate the overall performance of the kNN model, statistical measures (accuracy, specificity, sensitivity) were averaged.
Outcome measures: Accuracy of CT and MRI correlated with surgical findings and results.
Main Outcome Measures: Accuracy of self-control of slow cortical potentials (percentage of correct responses).
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Sophisticated variants of this basic testing procedure have been developed using photoelectric cells or interferometers to obtain greater measuring accuracy.
The measuring accuracy is 0.283 μm.
Thus, the measuring accuracy for graph matching can be improved.
The volume change was measured with a KM-6 cathetometer (measuring accuracy ±0.001 mm).
OR (4) "Measuring accuracy of the sub dimension "significance" can be assessed as good".
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