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First, retaining one feature class in the classifier, we can get separate F-scores based on these features.
You can find more information on these features for iOS at www.apple.com/accessibility/ios.com/accessibility/ios
More detailed discussion on these features will be given later.
It is worth investigating the averaging effect on these features.
Cavity classification is then performed based on these features.
The feature vector is then generated based on these features.
Based on these features, MANEC arising in BE was diagnosed.
Some will execute well on these features, most will not.
And classifier is designed based on these features.
Note that this does not depend on these features of the environment being co-extensional.
Based on these features, different properties of the product may be generated during microwave synthesis progress.
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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