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Exact(8)
For any given data, such an inequality will, of course, hold with some constants depending on (N) and the data set.
We compute the marginal distribution since, for any given data (here, and ), (13). is specified in the conditional probability table for the node, is defined from the frequency of occurrence of data in the training set and is uniform in most cases.
Setting the derivative to zero and solving for θ arrives at an expression for the value that minimises Eq 1 for any given data set and values of λ and k: θ λ, k = λ k − 2 ∑ x ∈ data x k − 2 T observed x e − x λ k × ∑ x ∈ data x k − 2 T observed x e − x λ k 2 − 1 (2).
The relative increase of variance due to substitution of missing data can be calculated for any given data [ 5].
The normalized value is defined as the value divided by the maximum value for any given data set.
Here we design a general procedure for constructing the null distribution of tightness for any given data randomization scheme.
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Two-dimensional (2-D) hierarchical agglomerative clustering (experiments × genes) remains a standard approach for gaining an overview of any given data structure.
Second, the quality of the data comprising any particular element is made up of several factors, here termed attributes, that ultimately determine the ability to use any given data element for CER.
in the cache for a given data file.
Picking the right model for a given data set has significant implications for business decisions.
A drawback of the GMMs is the parameter estimation for a given data set.
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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