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Macskassy and Provost [4] propose the weighted-vote relational neighbor (WvRN) classifier by making predictions based on the class distribution of a certain node's neighbors.
It is a technique that checks if a specific distribution of a certain observed event's frequency in a sample is suitable for that sample or not.
The concept of material feature is defined as the specified material distribution of a certain sub-region within a solid, which is a high level abstraction of design intent.
The Raman images showing the distribution of a certain constituent were calculated by integrating the corresponding Raman band region.
These 'MS images' or 'selected ion images' 1 represent the spatial intensity distribution of a certain m/ z signal, which can be assigned to a certain compound.
In brief, the larger the t, the larger the difference between the two peaks (i.e. modes) in the distribution of a certain gene signal profile within the cohort.
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If the model predicts the experimental results well, the F value should be greater than the tabulated value of F distribution for a certain number of degrees of freedom in the model at a level of significance α.
If the proposed model be a good predictor of the experimental results, the F value should be greater than the tabulated value of the F distribution for a certain number of degrees of freedom in the model at the level of significance α.
For the proposed model to be a good predictor of the experimental results, the F model value should be greater than the calculated value of the F distribution for a certain number of degrees of freedom in the model at the level of significance α.
A necessary and sufficient condition for a given pattern of selective influences is provided by the Joint Distribution Criterion, according to which the problem of "what influences what" is equivalent to that of the existence of a joint distribution for a certain set of random variables.
How is the 'purity' of a scale-free distribution measured and how much more often does one need to add nodes than edges to get distributions of a certain 'purity'purity
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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