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K-means clustering aims to partition n observations into k clusters in which each observation belongs to the cluster with the nearest mean.
npm install --save ml-kmeans
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
}
*/
FAQs
K-Means clustering
We found that ml-kmeans demonstrated a not healthy version release cadence and project activity because the last version was released a year ago. It has 7 open source maintainers collaborating on the project.
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