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The two metrics were evaluated in three independent studies: a classroom-based evaluation with two groups of students, a qualitative feedback from three industry projects, and a quantitative evaluation using 61 industry projects.
Individual metrics were evaluated based on relative scores on two sets of evaluation factors.
Seven distinct landscape metrics were evaluated.
In this work, probabilisitic and deterministic error metrics were evaluated for the two methods.
Multiple descriptors and distance metrics were evaluated for their ability to select diverse subsets from parent databases.
The various metrics were evaluated for their ability to represent error and their suitability for use in model improvement frameworks.
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Lexical metric composition [24] was used, with the routing metrics being evaluated in the following order: AccLQ, H, CU i. Algorithm 1 compares two routes based on the respective metrics.
The performance metrics are evaluated over four crafted utility settings.
Performance metrics are evaluated to model possible embedded system implementations.
Two different metrics are evaluated: accuracy and maxF1.
Mean value of the metrics are evaluated to all the images of background dataset.
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attributes were evaluated
arrangements were evaluated
measures were evaluated
criteria were evaluated
determinations were evaluated
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considerations were evaluated
parameters were evaluated
factors were evaluated
determinants were evaluated
metrics were considered
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metrics were computed
metrics were generated
metrics were conducted
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com