@thi.ng/k-means
Version:
k-means & k-medians with customizable distance functions and centroid initializations for n-D vectors
172 lines (131 loc) • 6.91 kB
Markdown
<!-- This file is generated - DO NOT EDIT! -->
<!-- Please see: https://github.com/thi-ng/umbrella/blob/develop/CONTRIBUTING.md#changes-to-readme-files -->
# 
[](https://www.npmjs.com/package/@thi.ng/k-means)
[](https://mastodon.thi.ng/@toxi)
> [!NOTE]
> This is one of 210 standalone projects, maintained as part
> of the [.ng/umbrella](https://github.com/thi-ng/umbrella/) monorepo
> and anti-framework.
>
> 🚀 Please help me to work full-time on these projects by [sponsoring me on
> GitHub](https://github.com/sponsors/postspectacular). Thank you! ❤️
- [About](#about)
- [Status](#status)
- [Installation](#installation)
- [Dependencies](#dependencies)
- [Usage examples](#usage-examples)
- [API](#api)
- [Authors](#authors)
- [License](#license)
## About
k-means & k-medians with customizable distance functions and centroid initializations for n-D vectors.
In addition to the main
[`kmeans()`](https://docs.thi.ng/umbrella/k-means/functions/kmeans.html)
implementation, the following k-means centroid initialization functions are
provided (can also be used in isolation to extract cluster centroids):
- [`kmeansPlusPlus()`](https://docs.thi.ng/umbrella/k-means/functions/kmeansPlusPlus.html)
- [`meanCut()`](https://docs.thi.ng/umbrella/k-means/functions/meanCut.html)
- [`medianCut()`](https://docs.thi.ng/umbrella/k-means/functions/medianCut.html)
## Status
**BETA** - possibly breaking changes forthcoming
[Search or submit any issues for this package](https://github.com/thi-ng/umbrella/issues?q=%5Bk-means%5D+in%3Atitle)
## Installation
```bash
yarn add .ng/k-means
```
ESM import:
```ts
import * as kmeans from "@thi.ng/k-means";
```
Browser ESM import:
```html
<script type="module" src="https://esm.run/@thi.ng/k-means"></script>
```
[JSDelivr documentation](https://www.jsdelivr.com/)
For Node.js REPL:
```js
const kmeans = await import("@thi.ng/k-means");
```
Package sizes (brotli'd, pre-treeshake): ESM: 1.10 KB
## Dependencies
- [.ng/api](https://github.com/thi-ng/umbrella/tree/develop/packages/api)
- [.ng/distance](https://github.com/thi-ng/umbrella/tree/develop/packages/distance)
- [.ng/errors](https://github.com/thi-ng/umbrella/tree/develop/packages/errors)
- [.ng/random](https://github.com/thi-ng/umbrella/tree/develop/packages/random)
- [.ng/vectors](https://github.com/thi-ng/umbrella/tree/develop/packages/vectors)
Note: .ng/api is in _most_ cases a type-only import (not used at runtime)
## Usage examples
Two projects in this repo's
[/examples](https://github.com/thi-ng/umbrella/tree/develop/examples)
directory are using this package:
| Screenshot | Description | Live demo | Source |
|:-----------------------------------------------------------------------------------------------------------------------|:----------------------------------------------------------------------------|:------------------------------------------------------|:-----------------------------------------------------------------------------------|
| <img src="https://raw.githubusercontent.com/thi-ng/umbrella/develop/assets/examples/dominant-colors.png" width="240"/> | Color palette generation via dominant color extraction from uploaded images | [Demo](https://demo.thi.ng/umbrella/dominant-colors/) | [Source](https://github.com/thi-ng/umbrella/tree/develop/examples/dominant-colors) |
| <img src="https://raw.githubusercontent.com/thi-ng/umbrella/develop/assets/examples/kmeans-viz.jpg" width="240"/> | k-means clustering visualization | [Demo](https://demo.thi.ng/umbrella/kmeans-viz/) | [Source](https://github.com/thi-ng/umbrella/tree/develop/examples/kmeans-viz) |
## API
[Generated API docs](https://docs.thi.ng/umbrella/k-means/)
Example usage: Clustering cities by lat/lon location
```ts tangle:export/readme.ts
import { HAVERSINE_LATLON } from "@thi.ng/distance";
import { kmeans, meansLatLon } from "@thi.ng/k-means";
// data sourced from:
// https://github.com/OpenDataFormats/worldcities/blob/master/src/data/cities.json
const cities = [
{ id: "anchorage", latlon: [61.21806, -149.90028] },
{ id: "berlin", latlon: [52.52437, 13.41053] },
{ id: "boston", latlon: [42.35843, -71.05977] },
{ id: "calgary", latlon: [51.05011, -114.08529] },
{ id: "cape town", latlon: [-33.92584, 18.42322] },
{ id: "detroit", latlon: [42.33143, -83.04575] },
{ id: "harare", latlon: [-17.82772, 31.05337] },
{ id: "london", latlon: [51.50853, -0.12574] },
{ id: "manila", latlon: [14.6042, 120.9822] },
{ id: "nairobi", latlon: [-1.28333, 36.81667] },
{ id: "new york", latlon: [40.71427, -74.00597] },
{ id: "paris", latlon: [48.85341, 2.3488] },
{ id: "philadelphia", latlon: [39.95233, -75.16379] },
{ id: "portland", latlon: [45.52345, -122.67621] },
{ id: "seoul", latlon: [37.566, 126.9784] },
{ id: "shanghai", latlon: [31.22222, 121.45806] },
{ id: "tokyo", latlon: [35.6895, 139.69171] },
{ id: "vancouver", latlon: [49.24966, -123.11934] },
{ id: "vienna", latlon: [48.20849, 16.37208] },
{ id: "windhoek", latlon: [-22.55941, 17.08323] },
];
// cluster based on lat/lon
const clusters = kmeans(
5,
cities.map((x) => x.latlon),
{
// custom centroid calc for geo locations
// https://docs.thi.ng/umbrella/k-means/functions/meansLatLon.html
strategy: meansLatLon,
// custom distance function for geo location (default: DIST_SQ)
dist: HAVERSINE_LATLON,
}
);
// print each cluster
for (let c of clusters) {
console.log(c.items.map((i) => cities[i].id));
}
// [ 'manila', 'seoul', 'shanghai', 'tokyo' ]
// [ 'berlin', 'london', 'paris', 'vienna' ]
// [ 'boston', 'detroit', 'new york', 'philadelphia' ]
// [ 'cape town', 'harare', 'nairobi', 'windhoek' ]
// [ 'anchorage', 'calgary', 'portland', 'vancouver' ]
```
## Authors
- [Karsten Schmidt](https://thi.ng)
If this project contributes to an academic publication, please cite it as:
```bibtex
{thing-k-means,
title = "@thi.ng/k-means",
author = "Karsten Schmidt",
note = "https://thi.ng/k-means",
year = 2021
}
```
## License
© 2021 - 2025 Karsten Schmidt // Apache License 2.0