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By contrast, LMNN algorithm is aimed at the organization of the k-nearest neighbors to the same class, while examples from different classes are separated by a large margin [ 15, 17, 33, 34].
Specifically, the Mahanalobis distance is optimized with the goal that the k-nearest neighbors always belong to the same class while examples from different classes are separated by a large margin [ 34].
These transformations can improve significantly [ 17] in k Nearest Neighbors (KNN) [ 15] which are aimed to be organised to the same class, while examples from different classes are separated by a large margin [ 18, 19].
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Mr. Gold created two large bedrooms, separated by a large, long living-and-dining room.
MIMLwel assumes that highly relevant labels usually share common instances, and the underlying class means of bags for each label are separated with a large margin [ 18].
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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