runClara {CytoTree} | R Documentation |
Clustering a data matrix into k clusters
runClara( object, k = 25, metric = c("euclidean", "manhattan", "jaccard"), stand = FALSE, samples = 5, scale = TRUE, trace = 0, verbose = FALSE, ... )
object |
an CYT object |
k |
numeric. The number of clusters. It is required that 0 < k < n where n is the number of observations (i.e., n = nrow(x)). |
metric |
character. string specifying the metric to be used for calculating dissimilarities between observations. |
stand |
logical. Indicating if the measurements in x are standardized before calculating the dissimilarities. |
samples |
numeric. Say N, the number of samples to be drawn from the dataset. The default is N = 5, |
scale |
logical. Whether to use scaled data in kmeans. |
trace |
numberic. Indicating a trace level for diagnostic output during the algorithm |
verbose |
logical. Whether to print calculation progress. |
... |
Parameters passing to |
an CYT object with clara.id in meta.data
cyt.file <- system.file("extdata/cyt.rds", package = "CytoTree") cyt <- readRDS(file = cyt.file) cyt <- runClara(cyt, k = 25, verbose = TRUE)