Description Usage Arguments Details Value Author(s) See Also Examples

Run the base `kmeans`

function with the specified number of centers within `clusterRows`

.

1 2 3 4 | ```
KmeansParam(centers, ...)
## S4 method for signature 'ANY,KmeansParam'
clusterRows(x, BLUSPARAM, full = FALSE)
``` |

`centers` |
An integer scalar specifying the number of centers. Alternatively, a function that takes the number of observations and returns the number of centers. |

`...` |
Further arguments to pass to |

`x` |
A numeric matrix-like object where rows represent observations and columns represent variables. |

`BLUSPARAM` |
A KmeansParam object. |

`full` |
Logical scalar indicating whether the full k-means statistics should be returned. |

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 KmeansParam object `x`

,
users can simply call `x[[i]]`

or `x[[i]] <- value`

where `i`

is any argument used in the constructor.

The `KmeansParam`

constructor will return a KmeansParam 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`

;
the latter will contain the direct output of `kmeans`

.

Aaron Lun

`kmeans`

, which actually does all the heavy lifting.

1 2 3 | ```
clusterRows(iris[,1:4], KmeansParam(centers=4))
clusterRows(iris[,1:4], KmeansParam(centers=4, algorithm="Lloyd"))
clusterRows(iris[,1:4], KmeansParam(centers=sqrt))
``` |

bluster documentation built on Nov. 8, 2020, 8:29 p.m.

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