kmeanspp: Perform the k-means++ algorithm
In scregclust: Reconstructing the Regulatory Programs of Target Genes in scRNA-Seq Data
kmeanspp R Documentation
Perform the k-means++ algorithm
Description
Performs the k-means++ algorithm to cluster the rows of the input matrix.
Usage
kmeanspp(x, n_cluster, n_init_clusterings = 10L, n_max_iter = 10L)
Arguments
x
Input matrix (n x p)
n_cluster
Number of clusters
n_init_clusterings
Number of repeated random initializations
to perform
n_max_iter
Number of maximum iterations to perform in the k-means
algorithm
Details
Estimation is repeated
Value
An object of class stats::kmeans.
References
David Arthur and Sergei Vassilvitskii. K-Means++: The advantages
of careful seeding. In Proceedings of the Eighteenth Annual ACM-SIAM
Symposium on Discrete Algorithms, SODA '07, pages 1027––1035.
Society for Industrial and Applied Mathematics, 2007.
scregclust documentation built on April 4, 2025, 3:03 a.m.
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| kmeanspp | R Documentation |
Perform the k-means++ algorithm
Description
Performs the k-means++ algorithm to cluster the rows of the input matrix.
Usage
kmeanspp(x, n_cluster, n_init_clusterings = 10L, n_max_iter = 10L)
Arguments
x |
Input matrix (n x p) |
n_cluster |
Number of clusters |
n_init_clusterings |
Number of repeated random initializations to perform |
n_max_iter |
Number of maximum iterations to perform in the k-means algorithm |
Details
Estimation is repeated
Value
An object of class stats::kmeans.
References
David Arthur and Sergei Vassilvitskii. K-Means++: The advantages of careful seeding. In Proceedings of the Eighteenth Annual ACM-SIAM Symposium on Discrete Algorithms, SODA '07, pages 1027––1035. Society for Industrial and Applied Mathematics, 2007.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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