k-means++

Cluster multivariate data using the k-means++ algorithm.

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An efficient implementation of the k-means++ algorithm for clustering multivariate data. It has been shown that this algorithm has an upper bound for the expected value of the total intra-cluster distance which is log(k) competitive. Additionally, k-means++ usually converges in far fewer than vanilla k-means.

인용 양식

Laurent S (2026). k-means++ (https://kr.mathworks.com/matlabcentral/fileexchange/28804-k-means), MATLAB Central File Exchange. 검색 날짜: .

도움

도움 받은 파일: Kmeans Clustering

도움 준 파일: kmeans_varpar(X,k), Sparsified K-Means

카테고리

Help CenterMATLAB Answers에서 Statistics and Machine Learning Toolbox에 대해 자세히 알아보기

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버전 퍼블리시됨 릴리스 정보 Action
1.7.0.0

Fixed bug with 1D datasets (thanks Xiaobo Li).

1.6.0.0

Improved handling of overclustering (thanks Sid S) and added a screenshot.

1.5.0.0

Small bugfix.

1.4.0.0

Removed dependency on randi for R2008a or lower (thanks Cassie).

1.3.0.0

Even faster, even less code and also fixed a few small bugs.

1.0.0.0