K-Means clustering

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

A fast, efficient k-means clustering implementation in TypeScript

Javascript implementation of the K-means clustering algorithm.

k-means clustering in TypeScript

generate colour palettes from images using K-means clustering

Simple implementation of the k-means clustering method.

A WebAssembly implementation of the k-means clustering algorithm for color quantization and general vector-space clustering.

Implementation of the k-means clustering algorithm

A simple k-means clustering implement.

A K-Means clustering library for React / Vue / Angular / Typescript / Javascript, featuring K-Means++ initialisation and support for multiple runs to ensure optimal inertia

This code defines a kmeans function that takes a dataset (X), the number of clusters (k), and the maximum number of iterations as input. It initializes centroids randomly, assigns data points to the nearest centroid, and updates the centroids based on the

K-Means Clustering for Unsupervised Learning

k-means clustering for color images. Uses the kmeans_colors crate from https://crates.io/crates/kmeans_colors

Density Based Clustering in JavaScript

Extract dominant colors from images using k-means clustering - browser-only, no dependencies

A simple implementation of a single dimensional k-means-clustering algorithm.

A library for creating and managing embeddings with PCA and k-means clustering.

A simple unsupervised learning package for Node JS. Currently provides k-means clustering

K-Means clustering.