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The specificity of features is computed by comparing the feature values of the selected elements to the feature values of the entire dataset.
Figures 6 and 7 indicate the distribution of feature values of labeled points.
However, this approach is limited, as it ignores the actual feature values of the instances itself.
After the mapping step, we assign feature values of the k-th skeleton to the actual test person.
This is probably because the feature values of these three servers are very stable in the multi-dimensional space.
The algorithm provides a method to subdivide surfaces based on the feature values of elevation texture in the surfaces and the binary-tree of triangle.
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Fig. 4 Feature value of three servers.
The importance of a feature is computed by swapping the feature value of the fragment and re-classifying the compound.
In particular, all features in the dataset and the (mean) feature value of the currently selected element are presented.
Fig. 4 Feature value of three servers Step 2: Repeat for each Cloud server N ◦ Map each feature value of Cloud server to virtual model within specific range, which is defined in step1.
◦ Map each feature value of Cloud server to virtual model within specific range, which is defined in step1.
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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