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The variance explained by both models was slightly higher than 82% and the standard error of prediction was lower than 45%.
The prediction capability ((q_{ext}^{2} = 0.639text0.646)) of the RF models was slightly worse than that of the RVM models but obviously better than those of the other models.
The difference between the CCNB2 and clinicopathological models was slightly less convincing.
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Let's hope tomorrow's models are slightly more clothed.
The sedan's ride — for either 4-cylinder or V-6 models — is slightly firm.
My own research shows that in the oceans, the models are slightly under-predicting the rate of heating.
This year's models are slightly darker than their predecessors and have Western-inspired details like topstitching, yokes and snaps.
Predictions of minor road models are slightly better than major road models.
(The 4-gigger is lighter, and 80 and 160GB models are slightly bigger and even deadlier weapons).
Furthermore, for the DB2 database, the accent command durations of lexical models is slightly higher than those of automatic models.
Most of the developed ANN models were slightly capable to predict the discharge but most predictions were underestimating.
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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