UMAP

Uniform Manifold Approximation and Projection (UMAP) is a dimension reduction technique that can be used for visualization similarly to t-SNE, but also for general non-linear dimension reduction.

How It Works

Uniform Manifold Approximation and Projection (UMAP) constructs a high-dimensional graph representation of the data and optimizes a low-dimensional graph to be as structurally similar as possible, grounded in Riemannian geometry.

Why or When to Use

An excellent, fast alternative to t-SNE that scales well to large datasets and tends to preserve both local and global data structures effectively.

Example

How-to (Code)

import * as druid from "@saehrimnir/druidjs";

const data = [
  /* ... multi-dimensional data ... */
];

// 1. Initialize the iterative algorithm
const umap = new druid.UMAP(data, { n_neighbors: 15, min_dist: 0.1 });

// 2. Compute the projection (e.g. 500 iterations)
const projection = umap.transform(500);

// Alternatively, use a generator for animation:
// for (const proj of umap.generator(500)) { ... }