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Table 1 shows computed prices, errors (difference between exact and computed prices), convergence rates and cpu timings.
To achieve the best performance model, a scoring table was proposed considering several factors including coefficient of determination, sum of errors, difference between training and testing errors, sum of residuals, deviation of predicted results from experimental one and complexity and generality of the models.
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In view of the risk of type I errors, differences in all analyses were considered significant at alpha ≤ 0.01.
In order to protect against Type I errors, differences in studied parameters were evaluated with the Bonferroni-corrected Mann-Whitney U test.
Error Difference t-cal Sig.
Figure 15 Error difference between before/after filtering.
(a, d) Angle error difference er EIAA angle - er IAA angle ; (b, e) power error difference er EIAA power - er IAA power ; (c, f) RTR of EIAA and IAA.
The prediction error (difference between actual and predicted endpoint value, optionally the squared-error for regression).
error difference 95% Confidence interval of the difference Lower Upper Was the acadmic content valuable?
Error Difference 95% Confidence Interval of the Difference F Sig. t df Sig.
The prediction error difference (error simple-linear − support-vector ) of two regression approaches for the Caco-2 dataset is selected.
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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