↑S↓↑p↓↑i↓↑n↓ ↑D↓↑r.↓
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A bit of graph visualization today #machinelearning #Datascience #networks #embedding

Many dimensionality reduction techniques rely on approximating relationship between samples by distances. Picking the right distance is primordial, but I'm now exploring edges vs triangles.
03:34 PM - Mar 12, 2023
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↑S↓↑p↓↑i↓↑n↓ ↑D↓↑r.↓
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In response to ↑S↓↑p↓↑i↓↑n↓ ↑D↓↑r.↓.
Those two graphs attempts to accomplish the same thing: extract triangular relationships in the data: groups of 3 samples that are closely linked together.
03:35 PM - Mar 12, 2023
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