R: Partitioning around medoids

PamParam-class {bluster}

R Documentation

Partitioning around medoids

Description

Partition observations into k-medoids as a more robust version of k-means.

Usage

PamParam(
  centers,
  metric = NULL,
  medoids = NULL,
  nstart = NULL,
  stand = NULL,
  do.swap = NULL,
  variant = NULL
)

## S4 method for signature 'ANY,PamParam'
clusterRows(x, BLUSPARAM, full = FALSE)

Arguments

`centers`	An integer scalar specifying the number of centers. Alternatively, a function that takes the number of observations and returns the number of centers.
`metric, medoids, nstart, stand, do.swap, variant`	Further arguments to pass to `pam`. Set to the function defaults if not supplied.
`x`	A numeric matrix-like object where rows represent observations and columns represent variables.
`BLUSPARAM`	A PamParam object.
`full`	Logical scalar indicating whether the full PAM statistics should be returned.

Details

This class usually requires the user to specify the number of clusters beforehand. However, we can also allow the number of clusters to vary as a function of the number of observations. The latter is occasionally useful, e.g., to allow the clustering to automatically become more granular for large datasets.

To modify an existing PamParam object x, users can simply call x[[i]] or x[[i]] <- value where i is any argument used in the constructor.

Value

The PamParam constructor will return a PamParam object with the specified parameters.

The clusterRows method will return a factor of length equal to nrow(x) containing the cluster assignments. If full=TRUE, a list is returned with clusters (the factor, as above) and objects (a list containing pam, the direct output of pam).

Author(s)

Aaron Lun

Examples

clusterRows(iris[,1:4], PamParam(centers=4))
clusterRows(iris[,1:4], PamParam(centers=4, variant="faster", do.swap=FALSE))
clusterRows(iris[,1:4], PamParam(centers=sqrt))

[Package bluster version 1.2.1 Index]