init.centers {CEC} | R Documentation |
Cluster Center Initialization
Description
init.centers
automatically initializes the centers of the
clusters before running the Cross-Entropy Clustering algorithm.
Usage
init.centers(x, k, method = c("kmeans++", "random"))
Arguments
x |
A numeric matrix of data. Each row corresponds to a distinct
observation; each column corresponds to a distinct variable/dimension. It
must not contain |
k |
An integer indicating the number of cluster centers to initialize. |
method |
A character string indicating the initialization method to use. It can take the following values:
|
Value
A matrix with k
rows and ncol(x)
columns.
References
Arthur, D., & Vassilvitskii, S. (2007). k-means++: the advantages of careful seeding. Proceedings of the Eighteenth Annual ACM-SIAM Symposium on Discrete Algorithms, 1027–1035.
Examples
## See the examples provided with the cec() function.