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In graph partitioning [10], the database is partitioned with frequently used attributes, that is common partitioning key (wid).
They showed that naive Bayes machine learning methods outperform rule-based or decision tree learning methods and they showed, on the other hand, that the choice of learning methods used for defect predictions can be much more important than used attributes.
Grain (also known as resolution) and extent are among the most commonly used attributes when referring to scale.
Most of these studies [ 9, 20] have successfully used attributes of oscillations (i.e., levels of synchrony, fluctuation in amplitude) to link verbal processes with the left hemisphere and visual processes with the right hemisphere.
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Another frequently used attribute is cycle length, or fixed formulas for counting days of ovulation.
We here used attribute exploration as an open knowledge discovery method to unravel rules hidden in data and simulations.
It is not entering the online dating game but running a Facebook application that scans photographs of faces and tries to find matching images in its database, using attributes like skin color and chin angles.
The entities provide information about their states using attributes.
We now discuss using attributes as evidence to make trust decision.
XACML uses attributes to build policies thereby works great with ABAC.
Non-experts do not combine knowledge from different sources using attributes the way experts do.
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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