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The hyperparameters which give best performance results on the validation dataset are picked.
Predicted and observed deaths in the validation dataset are shown in Figure 1 by risk decile.
As shown in our results on validation dataset are in agreement with training dataset.
The percentages of correct SAS and MAS signal identification using the validation dataset are given in Table 2.
The MAPE values of the forecasts generated by the various models for the validation dataset are shown in Table 2.
Summary statistics for the estimated and true values in the validation dataset are shown in Table 1.
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The validation dataset was used to validate the models of the 300 Index and Site Index developed using the fitting dataset.
The validation dataset is employed to validate the final model for accuracy and to predict the limiting velocity required to prevent sedimentation in sewer systems.
Then, the validation dataset was used to validate the items' prioritisation and the two diagnostic trees.
The validation dataset is the difference between the full set and the training set.
The validation dataset was distributed among 48 sub-clusters of data.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com