https://github.com/daprice/swiftkmeansplusplus

Swift implementation of the k-means++ algorithm that can operate on any collection of SIMD vectors
https://github.com/daprice/swiftkmeansplusplus

Last synced: about 2 months ago
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Swift implementation of the k-means++ algorithm that can operate on any collection of SIMD vectors

• Host: GitHub
• URL: https://github.com/daprice/swiftkmeansplusplus
• Owner: daprice
• License: mit
• Created: 2024-07-30T22:29:42.000Z (5 months ago)
• Default Branch: main
• Last Pushed: 2024-07-30T22:32:11.000Z (5 months ago)
• Last Synced: 2024-10-01T16:03:34.672Z (3 months ago)
• Language: Swift
• Size: 6.84 KB
• Stars: 2
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# SwiftKMeansPlusPlus

Swift implementation of the *k*-means++ algorithm that can operate on a collection of SIMD vectors of any length.

## Overview

[k-Means](https://en.wikipedia.org/wiki/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++](https://en.wikipedia.org/wiki/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.