Initialize cluster centers using the k-means++ algorithm, which selects
centers with probability proportional to squared distance from existing
centers.
Usage
cluster.init(fdataobj, ncl, metric = "L2", seed = NULL)
Arguments
- fdataobj
An object of class 'fdata'.
- ncl
Number of clusters.
- metric
Metric to use. One of "L2", "L1", or "Linf".
- seed
Optional random seed.
Value
An fdata object containing the initial cluster centers.
Examples
t <- seq(0, 1, length.out = 50)
X <- matrix(rnorm(30 * 50), 30, 50)
fd <- fdata(X, argvals = t)
init_centers <- cluster.init(fd, ncl = 3)