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This underprediction was also evident for the non-parametric models, and bias for these models was greater than that for parametric models (Fig. 5).
The table shows that the total accuracy of all of the models was greater than 80%, and when the number of trees was greater than 20, the total accuracy was greater than 85%.
Based on test datasets, the mean absolute percentage error for ANN and PCA-M5P models were 4%and12%2%, respectively, and the correlation coefficient for both models was greater than 0.98.
Although the data were not normal, we considered H significant if the difference between the −2 log likelihoods for the two models was greater than 3.84 (χ value significant at α = 0.05).
As the lowest Akaike Information Criterion (AIC) of the 3-parameter models was greater than the lowest of the 2-parameter models, only models with up to 3 parameters were fitted.
If the prediction returned by any of the 53 models was greater than an established threshold, the document was labelled with the CTD action term corresponding to that model.
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In all placements, the compressed displacement in the experimental models and FEA models was greatest with buccal loading and smallest with central loading at the three loading points.
Training prediction accuracy by all models is greater than 70%%.
R2 values of the models were greater than 0.89.
However, the stresses generated by the I-RME models were greater than the RME model.
It can be observed that the prediction accuracy by all models is greater than 70%%.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com