Finds the isolated clusters from a similarity/connectivity matrix.
The input could be a matrix (array of arrays) or it could be a single array containing the values of the upper triangular of that matrix.
By default the function returns a clustering matrix: It is a binary row wise matrix, where each row has n components. The ones at row i and column j indicates that element j belong to cluster i.
$ npm install ml-simple-clustering
import { simpleClustering } from 'ml-simple-clustering';
const clusters = simpleClustering(dataMatrix, options);In order to get a general idea of the problem you could also check the Wikipedia article.
const { simpleClustering } = require('ml-simple-clustering');
let matrix = [
[1, 2, 0, 0],
[1, 2, 0, 0],
[0, 0, 3, 4],
[0, 0, 5, 6],
];
let clusters = simpleClustering(matrix, {
threshold: 0,
out: 'values',
});
console.log(`clusters = ${clusters}`);
/**
clusters = [
[
[1, 2],
[1, 2],
],
[
[3, 4],
[5, 6],
],
]
*/