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Experimental result shows that EEMD-bagging-NN, EEMD-cross validation-NN, and EEMD-CV-bagging-NN models performance are a notch above EEMD-NN and significantly higher than the single-NN model.
Efforts to improve these models' performance are needed, but are limited by a lack of a gold standard for asthma development in children.
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The models performance was stable in larger data sized problems.
Models' performance was assessed through discrimination and calibration.
As is typical with predictive modeling, our models' performance is affected by the percentage of uncontrolled asthma in AST assessments.
Assessment measures of model performance are summarized in Table 3.
Differences in model performance are difficult to discern.
Three examples of the model performance are shown.
As observed, PESQ and E-model performance are most sensitive to wireless-VoIP distortions.
The distributions of maximum model performance are calculated in the following way.
The statistics of overall model performance are summarized in Table 2.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com