# umap-learn

## Uniform Manifold Approximation and Projection

Description

Uniform Manifold Approximation and Projection (UMAP) is a dimension reduction technique that can be used for visualisation similarly to t- SNE, but also for general non-linear dimension reduction. The algorithm is founded on three assumptions about the data: 1. The data is uniformly distributed on a Riemannian manifold;

2. The Riemannian metric is locally constant (or can be

approximated as such);

3. The manifold is locally connected.

From these assumptions it is possible to model the manifold with a fuzzy
topological structure. The embedding is found by searching for a low
dimensional projection of the data that has the closest possible
equivalent fuzzy topological structure.Upload more screenshots

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Homepage

https://github.com/lmcinnes/umap

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