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.

| argument | description | | ---: | :--- | | values | An iterable of the values to be clustered. | | clustersCount | Nhe number of the clusters. | | distance | A function to calculate the distance between two values. | | map | A function to map the values. | | maxIterations | The maximum number of iterations until the convergence. | | mean | A function to calculate the mean value. | | random | A function as the pseudo-random number generator. |

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']]