kmeans_varpar(X,k)
Implementation of K-means with Variance Partitioning initialization. Variance Partitioning initialization is a deterministic way of initializing the data centroids, thus producing results that are repeatable and reproducible, without having to resort to tricks like seeding the pseudorandom number generator.
引用
Stefan Philippo Pszczolkowski Parraguez (2024). kmeans_varpar(X,k) (https://www.mathworks.com/matlabcentral/fileexchange/57229-kmeans_varpar-x-k), MATLAB Central File Exchange. 取得済み .
MATLAB リリースの互換性
プラットフォームの互換性
Windows macOS Linuxカテゴリ
- AI, Data Science, and Statistics > Statistics and Machine Learning Toolbox > Cluster Analysis and Anomaly Detection >
タグ
謝辞
ヒントを得たファイル: k-means++
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!バージョン | 公開済み | リリース ノート | |
---|---|---|---|
1.0.1.0 | Removed loop that made sure that the number of returned centrers is equal to the specified k. This is arguably not necessary and since variance partitioning provides a deterministic result, there is potential for getting trapped in an infinite loop.
|
||
1.0.0.0 |