daprice/SwiftKMeansPlusPlus
Swift implementation of the k-means++ algorithm that can operate on any collection of SIMD vectors
Overview
k-Means is an algorithm for partitioning a collection of points into clusters based on the cluster with the nearest mean value to each point. k-Means++ is an improved algorithm for choosing the initial cluster centers to avoid suboptimal clustering.
This library contains extensions to Collection that perform k-Means++ clustering on SIMD values of any length, which can represent points in Euclidean space, colors in formats like RGB or HSV, or just about anything else.
Package Metadata
Repository: daprice/SwiftKMeansPlusPlus
Stars: 3
Forks: 0
Open issues: 0
Default branch: main
Primary language: swift
License: MIT
README: README.md