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Fig. 11 Single room dataset evaluation.
In this paper, we propose a new dataset evaluation method using the R-value measure.
This measure, which is often used in imbalance dataset evaluation studies, is a metric that combines both the sensitivity and specificity by calculating their geometric mean.
Single dataset evaluation is almost always a valuable precursor to evaluation of replicates because, typically, a second replicate is generated after a successful first one.
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The large dataset evaluations show that MetFrag2.2 is suitable for high-throughput workflows, with a relatively quick runtime.
This substantial increase in the number of targets for safety assessment makes full dataset evaluations an untenable proposition from an animal testing perspective as well as from simple consideration of resources and timeliness.
Evaluation dataset: for the evaluation dataset, we collected 6 months of PubMed log data (February, April, May, June, July and August, 2009), consisting of more than 333 million user queries, 329 million abstract views in 144 million user sessions.
Implementation and horizontal scalability of model construction and route prediction module are evaluated on the real dataset and evaluation results are discussed.
We also use synthetic dataset for evaluation.
In KITTI dataset webpage6, evaluation results are listed.
The details of the implementation, dataset, and evaluation results will be shown here.
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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