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A Julia package for multivariate statistics and data analysis (e.g. dimension reduction)

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umap is a new dimensionality reduction manifold learning technique UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction https://github.com/lmcinnes/umap

This might be a naive question but I am unable to understand how to use metric MDS. When following the examples in the documentation, I only get classical MDS out....

Currently the pipeline for MDS is `X -> D -> G -> M`, where `X` is a coordinate representation of the data, `D` is the pairwise distance matrix, `G` is...