kmeans_varpar(X,k)

Implementation of K-means with Variance Partitioning initialization

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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.

인용 양식

Stefan Philippo Pszczolkowski Parraguez (2026). kmeans_varpar(X,k) (https://kr.mathworks.com/matlabcentral/fileexchange/57229-kmeans_varpar-x-k), MATLAB Central File Exchange. 검색 날짜: .

도움

도움 받은 파일: k-means++

카테고리

Help CenterMATLAB Answers에서 Cluster Analysis and Anomaly Detection에 대해 자세히 알아보기

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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.
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