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Each model was evaluated using a10-fold cross validation.
Each model was evaluated on a training set.
Each model was evaluated with and without correction for blood volume fraction (VB).
Each model was evaluated on 10,000 batch random samples, with 25, 50, 100, 500 and 1,000 sample sizes.
Each model was evaluated under loads of 40, 100, 200, 400, and 800 N to determine the distribution of occlusal forces on the teeth and implants.
Each model was evaluated for goodness-of-fit using adjusted R 2, and comparisons were made between models using the Akaike information criterion (AIC).
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Each model is evaluated using two metrics: mean firing rate and modulation gain.
The accuracy of each model is evaluated according to the level of proximity to the oscillograms and conclusions are drawn about the effectiveness of each modelling approach.
Each model is evaluated for its ability to predict correctly experimental small angle X-ray scattering data and the radius of gyration (Rg) for the hexameric pullulan oligomer (G3)2.
Moreover for SHED descriptors, the similarity of A and B is given by Eq. 2: begin{aligned} S_{A, B} = 1 - frac{DIST A, B)}{20sqrt{10}}, end{aligned} (2 where DIST A, B) denotes the Euclidean distance between A and B. The performances of each model were evaluated with respect to accuracy, precision, sensitivity, specificity and (F_beta{textMeasure) as shown in the Eqs.
Finally, the performance of each generated model was evaluated using numerical analysis, and it was confirmed that its system efficiency has indeed improved.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com