Multidimensional scaling (MDS) is a statistical technique used for analyzing and visualizing similarities or dissimilarities between data points. Its primary goal is to represent high-dimensional data in lower dimensions (typically two or three) while preserving the pairwise distances between the points as much as possible. This makes MDS particularly useful for exploring data patterns and relationships in a way that is more interpretable for human analysis.
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