Umap in r

1. What is UMAP used for?
2. What is the difference between t-SNE and UMAP?
3. What package is UMAP?
4. What does UMAP mean?

What is UMAP used for?

UMAP is an algorithm for dimension reduction based on manifold learning techniques and ideas from topological data analysis. It provides a very general framework for approaching manifold learning and dimension reduction, but can also provide specific concrete realizations.

What is the difference between t-SNE and UMAP?

In another word: while t-SNE moves the graph point-to-point from high to low dimensional space, UMAP makes a fuzzy, but topologically similar graph and compresses it into a lower dimension.

What package is UMAP?

umap: Uniform Manifold Approximation and Projection

This package provides an interface for two implementations. One is written from scratch, including components for nearest-neighbor search and for embedding.

What does UMAP mean?

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.