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The highest performance of each data set is shown in bold.
Particularly interesting were the findings related to the performance of each data delivery technology used (the FCC, presumably looking at this from the consumer's viewpoint refers to this as "access technology").
Different from issues of the MISO wiretap channel in [6, 47 49], we focus on the impact of the SIC order on the individual secrecy performance (i.e., secrecy performance of each data stream in this equivalent MISO wiretap channel model).
Table 2 summarizes the performance of each data source and discovery method that contributes to the HS1011 SVs.
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Furthermore, the effect of each non-dimensional parameter on the performance of each data-driven model is investigated.
First, we focus on the individual performance of each PF data source.
The performance of each baseline data set to assign individuals to their ecotype of origin across this range of mixture proportions was estimated as the proportion of individuals accurately assigned.
We then tested the performance of each marker in clustering data into MOTUs.
The F1 measure gave us a quantitative idea of the performance of each method on training data.
In order to evaluate the performance of each model on independent data in the absence of a validation set, 3CV was used.
All classifiers were embedded within a leave-one-out cross-validation (LOOCV) framework to estimate the generalisation performance of each classifier for novel data points.
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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