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The inner CV was used to train the SVM (i.e. estimate the parameters), and parameters with the smallest prediction error were used to predict the test data from the outer CV.
The cross-validation technique is used to find the best surrogate that has the smallest prediction variance.
CV -80% shows the smallest prediction errors and performed thus better than 10-fold CV and CV -40%.
Therefore, we can conclude that the AGB gives the smallest prediction error, so it is an attractive technique in group selection.
The weight is small if there is a high prediction error using that is, the median filter is to substitute the previously estimated motion vector with a neighboring vector which has the smallest prediction error.
We found that these simulation methods consistently produced the lowest imputation error and had the smallest prediction difference when the models used imputed laboratory values.
Similar(42)
Interestingly, using information only from line B1 to predict line B2 resulted in a comparatively smaller prediction accuracy than using only information from line B2 to predict line B1.
This preactivation, in turn, may hamper the differentiation between the actual action effect and the preactivation of the predicted effect, resulting in a smaller brain activity (i.e. smaller prediction error).
By contrast, the other models provide smaller prediction intervals.
The simple estimation method works relatively well for small prediction windows.
The designed predictor (mathbb {Q}) has asymptotically small prediction regret compared to (mathbb {P}) [29,30].
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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