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The coefficient of determination, root mean square error and variance account statistics were used as comparison criteria.
The very high prediction accuracy was examined by calculating indices such as variance account for, root mean square error and coefficient of determination.
The coefficient of determination (R2), the variance account for (VAF) and the root mean square error (RMSE) were calculated to check the prediction performance of the model.
The suitability of models and their robustness examined by the coefficient of determination (R2), and performance indices such as the mean absolute percentage error (MAPE), variance account for (VAF) and root mean square error (RMSE).
The performance capacity of the predictive models were evaluated based on the coefficient of determination (R2), the mean absolute percentage error (MAPE), the root mean square error (RMSE) and the variance account for (VAF).
Results of the simulated system for sufficient large number of independent runs validated the reliability and effectiveness of the given methods through different performance measures in terms of mean square error, variance account for, and Nash Sutcliffe efficiency.
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Fig. 5 Mediation and variance accounted for.
The results supported the hypotheses, with most variance accounted for by the GFP.
The variance accounted for by this two-dimensional model was 67.2% (dimension 1: 42.3% and dimension 2: 24.9%).
The variance accounted for by the two-dimensional model was 62.9% (dimension 1: 44.3% and dimension 2: 18.6%).
The largest amount of variance accounted for in both sections was the undifferentiated error.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com