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The content of this analysis and the categorization were discussed in depth with the research team.
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The categorization is defined even by means of the parameter that is usually.
The categorization was based on visual assessment of the MPS images.
The categorization is performed using multi-layer feed forward network in neural network.
The two variables used for the categorization are level of abstraction and the temporal characteristic of the model.
It is, however, worth pointing out that the categorization is not unique and should be used with caution, since some of the studies are essentially interdisciplinary.
The categorization is empirically warranted by means of participant orientation in both typical and deviant cases, demonstrating the robustness of the phenomena.
In accomplishing this goal, document clustering offers the advantage that an a priori knowledge of categories is not needed, therefore the categorization is completely unsupervised.
When a person knows only the superficial features, it is impossible to realize that the categorization is incorrect from a functional perspective.
For the other four scenarios, we will assume that the Web resource was analyzed and a representation of some features of the context of the categorization is available.
The categorization is in line with [1] and [2]; it also includes measures found in current policy intervention programs (see [3] and section 3).
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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