Abstract
Dimensionality reduction techniques, also called projections, are one of the main tools for visualizing high-dimensional data. To compare such techniques, several quality metrics have been proposed. However, such metrics may not capture the visual separation among groups/classes of samples in a projection, i.e., having groups of similar (same label) points
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