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Similar performance was seen in the test set.
where U is the user set in the test set.
Figure 21 Matching molecule in the test set.
On the other hand, the model classifies 100.00% of these compounds in the test set.
In addition, this model predicted adequately the compounds contained in the test set.
bThe reference did not report the prediction results of all compounds in the test set.
Table 4 shows a summary of the similarity in the test set.
After splitting the dataset, an item is randomly hidden from each session in the test set.
Participants were then shown each molecule in the test set, in a random order.
Every third compound of the dataset was included in the test set.
Hypothesis were used to establish classification in the test set, which is compared to known one.
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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