MDS

Multidimensional Scaling (MDS) is a means of visualizing the level of similarity of individual cases of a dataset.

How It Works

Multidimensional Scaling (MDS) takes a matrix of pairwise distances and finds a configuration of points in low-dimensional space such that the distances between the points are preserved as closely as possible.

Why or When to Use

Use MDS when you only have distance/dissimilarity data between objects rather than feature vectors, and you want a simple global preservation of these spatial distances.

Example

How-to (Code)

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

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

// 1. Initialize the algorithm
const mds = new druid.MDS(data);

// 2. Compute the projection
const projection = mds.transform();