ClaraParam-class {bluster} | R Documentation

## Clustering Large Applications

### Description

Run the CLARA algorithm, an extension of the PAM method for large datasets.

### Usage

    ClaraParam(
      centers,
      metric = NULL,
      stand = NULL,
      samples = NULL,
      sampsize = NULL
    )

    ## S4 method for signature 'ANY,ClaraParam'
    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, stand, samples, sampsize` | Further arguments to pass to `clara`. Set to the function defaults if not supplied.
`x` | A numeric matrix-like object where rows represent observations and columns represent variables.
`BLUSPARAM` | A ClaraParam 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 ClaraParam object `x`, users can simply call `x[[i]]` or `x[[i]] <- value` where `i` is any argument used in the constructor.

Note that `clusterRows` will always use `rngR=TRUE`, for greater consistency with other algorithms of the FixedNumberParam class; and `pamLike=TRUE`, for consistency with the PAM implementation from which it was derived.

### Value

The `ClaraParam` constructor will return a ClaraParam 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 `clara`, the direct output of `clara`).

### Author(s)

Aaron Lun

### See Also

`clara`, which actually does all the heavy lifting.

PamParam, for the original PAM algorithm.

### Examples

    clusterRows(iris[,1:4], ClaraParam(centers=4))
    clusterRows(iris[,1:4], ClaraParam(centers=4, sampsize=50))
    clusterRows(iris[,1:4], ClaraParam(centers=sqrt))

[Package bluster version 1.4.0 Index]