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A higher value of consensus rate increases the precision of the method at the cost of decreased sensitivity.
For example, average thresholds 0.3, 0.4, and 0.5 have higher values of precision and recall than thresholds 0.6 and 0.7.
Apparently, (F_{1}) is a harmonic mean between precision and recall, and a high value of (F_{1}) ensures reasonably a high balance between precision and recall.
Thinkers see themselves as efficient and place a high value on thoroughness and precision.
This variable gets a high value in occupations that demand physical precision.
A high value was placed on precision and physical detail; revelation came slow and in a low key.
A high value for the item information at a given level of cognitive impairment implies that the item measures that level of cognitive impairment with high precision.
In this figure, a higher TMscore value indicates a higher degree of precision and/or length in the alignment.
It allows to dynamically select BCs that provide a higher level of precision (and F1 value) for target individuals, and a significantly smaller difference between desired and actual fpr.
A small value of gives real-time (online) responses with an acceptable precision while a high value requires more processing time but gives better retrieval performance.
For example, the precision is as high as 84.7% when the recall maintains a relatively high value of 45%.
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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