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While the PE of the independent test set quantifies the overall model performance, rating the reliability of an individual prediction is of importance in decision making.
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This approach led to the identification of the most predictive linear model for each CG-CAHperformanceance rating (eg, [1] overall satisfaction; [2] recommendation of the physician; [3] surgeon respect; and [4] clarity of the surgeon's explanation) regressed on all PULSE scores with which there was a significant bivariate relationship.
Our calibration outputs for monthly simulation for the period from 1976 to 1984 showed a good model performance for flow rates with NSE and PBIAS values of 0.76 and −11.80, respectively; also a good model performance for sediment concentration with NSE and PBIAS values of 0.69 and 7.12, respectively.
Some have attempted to incorporate amino acid substitution biases into models of codon evolution and have shown improved model performance versus the single rate model.
Predicted water and sediment concentrations of PAHs (SI Table S7) were used in the food web model to demonstrate overall model performance using estimated emission rates and physiochemical parameters without corrections or calibrations using water, sediment, or other measurements.
We used the half-life of 2.3 years estimated using a subpopulation of 200 participants from the C8 Health Project (Bartell et al. 2010) in an alternative analysis, to compare the model performance with different elimination rates.
For classification trees, model performance was assessed by misclassification rates.
The work reported in this paper extends previous research by comparing the performance of various data fusion neural network architectures and assessing model performance for various probe vehicle penetration rates and loop detector configurations.
When we applied the ICD-10 coding algorithms to the hospital discharge data, we found similarities across frequencies, mortality rates, and overall model performance to ICD-9 coding algorithms.
The rate of improvement in the model performance decreased as model complexity increased.
Then, these plots can be summarized with their maximum values, and the increment in model performance can be described by the NRI at event rate.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com