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The signs of all statistically significant effects in both models were generally the same across the training and test samples and cohered with our intuition.
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Both models are generally superior than the Random Forest model on all vector sets.
Although our tests suggest that the docking results of both models are generally similar, even when the provided default parameters are used, users should be cautious about using the all-atom model with the default parameters.
Because the Canadian models were generally budget versions of American cars, Mr. St.
The 5-DOF models were generally superior to the 4-DOF models for the simulation.
Based on MAE, all models were generally similar, with KPLS showing a slightly greater inaccuracy.
For volume prediction, the three taper models were generally unbiased across tree size.
The differences between the crude and the adjusted models were generally minor (Table 5).
The models were generally adequate in describing the heterogeneous data set.
The findings for the SEM and logistic regression models were generally supportive of each other.
Differences between models were generally small except for RRPCA which gave considerably higher accuracies for B2.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com