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.
인용 양식
Stefan Philippo Pszczolkowski Parraguez (2024). kmeans_varpar(X,k) (https://www.mathworks.com/matlabcentral/fileexchange/57229-kmeans_varpar-x-k), MATLAB Central File Exchange. 검색됨 .
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- AI, Data Science, and Statistics > Statistics and Machine Learning Toolbox > Cluster Analysis and Anomaly Detection >
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받음: k-means++
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Start Hunting!버전 | 게시됨 | 릴리스 정보 | |
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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.
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1.0.0.0 |