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Visualizing Data using GTSNE

Published 3 Aug 2021 in cs.LG, cs.HC, math.OC, and stat.ML | (2108.01301v1)

Abstract: We present a new method GTSNE to visualize high-dimensional data points in the two dimensional map. The technique is a variation of t-SNE that produces better visualizations by capturing both the local neighborhood structure and the macro structure in the data. This is particularly important for high-dimensional data that lie on continuous low-dimensional manifolds. We illustrate the performance of GTSNE on a wide variety of datasets and compare it the state of art methods, including t-SNE and UMAP. The visualizations produced by GTSNE are better than those produced by the other techniques on almost all of the datasets on the macro structure preservation.

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