K-Means clustering

Super fast simple k-means and k-means++ clustering for unidimiensional and multidimensional data. Works in node and browser

Takes a set of points and partition them into clusters using the k-means algorithm.

K-means and hierarchical clustering

Node.js asynchronous implementation of the clustering algorithm k-means

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

A typescript implementation of the k-means algorithm with different customization capabilities.

node wrapper around python implementation of k-means using numpy

k-means & k-medians with customizable distance functions and centroid initializations for n-D vectors

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

k-means with k-means++-initialization

A fast, efficient k-means clustering implementation in TypeScript

k-means based dominant color extraction from images/pixel buffers

A tool for data PCA(Principle Component Analysis) and cluster(K-Means & K-Medoids).

Simple Javascript implementation of the k-means algorithm, for node.js and the browser

A JS/TS implementation of the k-means algorithm.

High-performance TypeScript clustering algorithms (K-Means, Spectral, Agglomerative) with TensorFlow.js acceleration and scikit-learn compatibility

Clusters an array of vectors into k clusters using k-means (using random initial centroids and Euclidean as the distance function).

Extends k-means to x-means implemented by node js

Generate a color palette from an image using K-means++