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Another method is to compute one score that is interpreted as the "total" subjective burden.
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The first approximation to a distributed problem in this scenario is to compute m centralized solutions, one for each node of the network, so the classical KLS problem could be written as: begin{array}{*{20}l} &underset{f_{j}inmathcal{H}_{K}}{min}sumlimits_{i=1}^{n} z_{i}-y_{i})^{2} z_{i}-y_{i}j=1}^{2}+sumlimitsVert f_{j} Vert_{mathcal{H}_{K}}^{2} end{array} (8).
The second is to compute a pair of nested grids, one coarse and one fine.
The crux of the method consists of two algorithms: one is to compute the regular set of the sequences of tokens produced by a nondeterministic Mealy automaton when the automaton processes elements of an input regular set.
First one is to compute cluster prototypes, v i for each cluster i. Cluster prototypes refer to the average values of features of member objects (real data, z k ), weighted by membership degree of the object.
One option is to compute the Normalized Difference Vegetation Index (NDVI) from satellite images in a GIS environment.
One solution is to compute a unique prototype trajectory for each motion pattern, by agglomerating the previously observed trajectories.
One approach is to compute J({ k}) for every feature k by training a separate SVM for each feature k.
One option is to compute this gain or influence for each remaining feature k, by retraining the SVM.
One choice is to compute an unweighted average of (observed) ORs of all the tests the paper studied, and use it as the OR of that paper.
To evaluate mapper robustness, one method is to compute metrics (here precision, recall, and F-measure) through a benchmark formed by simulated reads for which their original location in the genome and the number and type of introduced errors are known.
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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