@seregpie/k-means-plus-plus v2.0.1

KMeansPlusPlus

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

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

Returns the clustered values as an array of arrays.

dependencies

• KMeans
• JustMyLuck

setup

npm

npm install @seregpie/k-means-plus-plus

ES module

import KMeansPlusPlus from '@seregpie/k-means-plus-plus';

Node

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

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>
<script src="https://unpkg.com/@seregpie/k-means-plus-plus"></script>

The module is globally available as KMeansPlusPlus.

usage

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