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where the second term can be upper bounded by using the th dominant sample.
In Section 4.2, we will evaluate the tightness of the bound based on the th dominant sample.
If the bound using the th dominant sample drops below a predefined value then the number of samples needed to approximate BER can be obtained as follows: (33).
Since the sharpness of (32) depends on the value of the th dominant sample (it becomes sharp if the value of the th dominant sample is small), this expression can be used to estimate the number of dominant samples to be used for giving efficient bound on BER.
Furthermore, whether a dominant (sample A) or minor (sample C) group, gram-positive bacteria were detected by all three platforms with only minor variation between the three extraction methods.
This discrepancy is probably due to the difference in patient demographic characteristics (i.e. a female dominant sample with younger age in our study versus a male dominant sample with older age in the Korean study).
Similar(52)
where can be substituted by its approximation using the first dominant samples.
Figure 2 analyzes the accuracy of the bound obtained by the dominant samples.
We found tunable nonlinear optical behaviors, reverse saturation absorption in the amorphous-phase dominant samples, and saturation absorption in the nanocrystalline-phase dominant ones, under femtosecond laser excitation.
The chosen golden negative dataset has a variable impact on the prediction performance, and it can be artificially inflated by a bias towards dominant samples in the positive data.
The selection of golden standard negative dataset has an important impact on the prediction performance, and it can be artificially inflated by a bias towards dominant samples in the positive data.
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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