https://github.com/mljs/kmeans

K-Means clustering
https://github.com/mljs/kmeans

clustering kmeans

Last synced: 3 months ago
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K-Means clustering

• Host: GitHub
• URL: https://github.com/mljs/kmeans
• Owner: mljs
• License: mit
• Created: 2015-06-18T07:17:58.000Z (over 9 years ago)
• Default Branch: master
• Last Pushed: 2023-02-27T13:33:05.000Z (over 1 year ago)
• Last Synced: 2024-07-18T18:53:28.166Z (4 months ago)
• Topics: clustering, kmeans
• Language: TypeScript
• Homepage:
• Size: 1.39 MB
• Stars: 76
• Watchers: 15
• Forks: 14
• Open Issues: 6
• Metadata Files:
  • Readme: README.md
  • Changelog: CHANGELOG.md
  • License: LICENSE

Awesome Lists containing this project

• awesome - mljs/kmeans - K-Means clustering (TypeScript)
• awesome - mljs/kmeans - K-Means clustering (TypeScript)

README

        
# ml-kmeans

[K-means clustering][] aims to partition n observations into k clusters in which

each observation belongs to the cluster with the nearest mean.



  

    

  

  


    Maintained by Zakodium

  


[![NPM version][npm-image]][npm-url]

[![Test coverage][codecov-image]][codecov-url]

[![npm download][download-image]][download-url]

## Installation

`npm i ml-kmeans`

## [API Documentation](https://mljs.github.io/kmeans/)

## Example

```js

const { kmeans } = require('ml-kmeans');

let data = [

  [1, 1, 1],

  [1, 2, 1],

  [-1, -1, -1],

  [-1, -1, -1.5],

];

let centers = [

  [1, 2, 1],

  [-1, -1, -1],

];

let ans = kmeans(data, 2, { initialization: centers });

console.log(ans);

/*

KMeansResult {

  clusters: [ 0, 0, 1, 1 ],

  centroids: [ [ 1, 1.5, 1 ], [ -1, -1, -1.25 ] ],

  converged: true,

  iterations: 2,

  distance: [Function: squaredEuclidean]

}

*/

console.log(ans.computeInformation(data));

/*

[

  { centroid: [ 1, 1.5, 1 ], error: 0.5, size: 2 },

  { centroid: [ -1, -1, -1.25 ], error: 0.125, size: 2 }

]

*/

```

## Authors

- [Miguel Asencio](https://github.com/maasencioh)

## Sources

D. Arthur, S. Vassilvitskii, k-means++: The Advantages of Careful Seeding, in: Proc. of the 18th Annual

ACM-SIAM Symposium on Discrete Algorithms, 2007, pp. 1027–1035.

[Link to article](http://ilpubs.stanford.edu:8090/778/1/2006-13.pdf)

## License

[MIT](./LICENSE)

[npm-image]: https://img.shields.io/npm/v/ml-kmeans.svg?style=flat-square

[npm-url]: https://npmjs.org/package/ml-kmeans

[codecov-image]: https://img.shields.io/codecov/c/github/mljs/kmeans.svg?style=flat-square

[codecov-url]: https://codecov.io/github/mljs/kmeans

[download-image]: https://img.shields.io/npm/dm/ml-kmeans.svg?style=flat-square

[download-url]: https://npmjs.org/package/ml-kmeans

[k-means clustering]: https://en.wikipedia.org/wiki/K-means_clustering