@seregpie/k-means v2.0.1

KMeans

KMeans(values, means, {
  distance(value, otherValue) { /* euclidean distance */ },
  map(value) { /* identity */ },
  maxIterations: 1024,
  mean(...values) { /* centroid */ },
  random: Math.random,
})

Implementation of the k-means algorithm to partition the values into the clusters.

Returns the clustered values as an array of arrays.

dependencies

• JustMyLuck
• VectorMath

setup

npm

npm install @seregpie/k-means

ES module

import KMeans from '@seregpie/k-means';

Node

let KMeans = require('@seregpie/k-means');

browser

<script src="https://unpkg.com/just-my-luck"></script>
<script src="https://unpkg.com/@seregpie/vector-math"></script>
<script src="https://unpkg.com/@seregpie/k-means"></script>

The module is globally available as KMeans.

usage

Let the initial means be chosen randomly.

let vectors = [[1, 4], [6, 2], [0, 4], [1, 3], [5, 1], [4, 0]];
let clusters = KMeans(vectors, 3);
// => [[[1, 4], [0, 4]], [[6, 2], [5, 1], [4, 0]], [[1, 3]]]

Provide the initial means.

let vectors = [[1, 4], [6, 2], [0, 4], [1, 3], [5, 1], [4, 0]];
let centroids = [[0, 7], [7, 0]];
let clusters = KMeans(vectors, centroids);
// => [[[1, 4], [0, 4], [1, 3]], [[6, 2], [5, 1], [4, 0]]]

Provide a map function to convert a value to a vector.

let Athlete = class {
  constructor(name, height, weight) {
    this.name = name;
    this.height = height;
    this.weight = weight;
  }
  toJSON() {
    return this.name;
  }
};
let athletes = [
  new Athlete('A', 185, 72), new Athlete('B', 183, 84), new Athlete('C', 168, 60),
  new Athlete('D', 179, 68), new Athlete('E', 182, 72), new Athlete('F', 188, 77),
  new Athlete('G', 180, 71), new Athlete('H', 180, 70), new Athlete('I', 170, 56),
  new Athlete('J', 180, 88), new Athlete('K', 180, 67), new Athlete('L', 177, 76),
];
let clusteredAthletes = KMeansPlusPlus(athletes, [athletes[0], athletes[1]], {
  map: athlete => [athlete.weight / athlete.height],
});
console.log(JSON.parse(JSON.stringify(clusteredAthletes)));
// => [['A', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'K'], ['B', 'J', 'L']]