ml-kmeans

kmeans

K-means clustering in JavaScript

K-means clustering aims to partition n observations into k clusters in which each observation belongs to the cluster with the nearest mean.

Installation

npm install ml-kmeans

API Documentation

Example

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: 
   [ { centroid: [ 1, 1.5, 1 ], error: 0.25, size: 2 },
     { centroid: [ -1, -1, -1.25 ], error: 0.0625, size: 2 } ],
  converged: true,
  iterations: 1
}
*/

Test

npm install
npm test

Authors

• Miguel Asencio

License

MIT

Changelog

3.0.0 (2016-10-07)

Bug Fixes

• remove unneeded array creations in updateClusterID (b2957d5)

Features

• accepts distance function as parameter (68993a1)
• allows to compute a new array of points their cluster id (254f9a9)
• return a generator in the withIterations option (3b4c7c6)
• return the number of iteration done (75fd42e)
• returns the error and the size of each cluster (e85aab7)
• when maxIterations is 0, iterates until converge (220c828)

<a name="2.0.0"></a>