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It splits the content of the input file into training and test sets, creates a simplified solubility model, and tests the model using the test set.
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Throughout the book, they provide illustrations from history, ranging from ancient Sparta to Vichy France, and test the model against statistics gathered from cross-national data.
Among them, the data of A, B and C wells were used to constructing and testing the model, respectively.
A total number of 595 different data points of these compounds were used to train, validate and test the model.
Detailed hydrologic measurements were collected from two bioretention field sites in Nashville and Rocky Mount, North Carolina, to calibrate and test the model.
And people doing their physiological studies are now working through those kinds of variations in stimulus and attention field and so on, and testing the model's performance with all those different variations.
The first two were used to train and test the model while the third was spared to blind test and validate the model efficiency.
It applies to the models with potential variables for indicating the mutual relationships and testing the model convergence.
The SSP was implemented separately in two provinces, New Brunswick and British Columbia, and we calibrate and test the model separately for each province.
We isolate the effects of the increase in the maximum duration of benefits and test the model.
All of the tuples in the dataset are used for training and testing the model in this method.
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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