Description Usage Arguments Value References See Also Examples
Run a k-means partitioning analysis. This function is
used by discrete
in ‘gap’ mode to
automatically determine the range of ambiguous data. If
applied to such one-dimensional data, it uses an exact
algorithm from the Ckmeans.1d.dp package.
1 2 3 4 | ## S4 method for signature 'matrix,numeric'
run_kmeans(object, k, cores = 1L, nstart = 10L, ...)
## S4 method for signature 'numeric,numeric'
run_kmeans(object, k, cores = 1L)
|
object |
Numeric vector or matrix. |
k |
Numeric vector. Number of clusters requested. |
nstart |
Numeric scalar. Ignored if
‘Ckmeans.1d.dp’ is called. Otherwise passed to
|
cores |
Numeric scalar indicating the number of cores to use. |
... |
List of optional arguments passed to
|
S3 object of class kmeanss
, basically a named list
of kmeans
objects.
Wang, H., Song, M. 2011 Ckmeans.1d.dp: Optimal k-means clustering in one dimension by dynamic programming. The R Journal 3, p. 29–33.
stats::kmeans Ckmeans.1d.dp::Ckmeans.1d.dp
Other kmeans-functions: borders
,
calinski
,
hist.Ckmeans.1d.dp
,
hist.kmeans
, hist.kmeanss
,
plot.kmeanss
, to_kmeans
,
1 2 3 4 |
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.