clusplot.partition {cluster} | R Documentation |

Clusplot (Clustering Plot) method for an object of class `partition`

.

## S3 method for class 'partition': clusplot(x, main = NULL, dist = NULL, ...)

`x` |
an object of class `"partition"` , e.g. created by the functions
`pam` , `clara` , or `fanny` . |

`main` |
title for the plot; when `NULL` (by default), a title
is constructed, using `x$call` . |

`dist` |
when `x` does not have a `diss` nor a
`data` component, e.g., for ```
pam(dist(*),
keep.diss=FALSE)
``` , `dist` must specify the dissimilarity for the
clusplot. |

`...` |
all optional arguments available for the
`clusplot.default` function (except for the `diss`
one) may also be supplied to this function. Graphical parameters
(see `par` ) may also be supplied as arguments to this
function. |

This `clusplot.partition()`

method relies on
`clusplot.default`

.

If the clustering algorithms `pam`

, `fanny`

and `clara`

are applied to a data matrix of observations-by-variables then a
clusplot of the resulting clustering can always be drawn. When the
data matrix contains missing values and the clustering is performed
with `pam`

or `fanny`

, the dissimilarity
matrix will be given as input to `clusplot`

. When the clustering
algorithm `clara`

was applied to a data matrix with NAs
then clusplot will replace the missing values as described in
`clusplot.default`

, because a dissimilarity matrix is not
available.

An invisible list with components

`Distances` |
When option lines is 1 or 2 we optain a k by k matrix (k is the number of clusters). The element at row j and column s is the distance between ellipse j and ellipse s. If lines=0, then the value of this component is NA. |

`Shading` |
A vector of length k (where k is the number of clusters), containing the amount of shading per cluster. Let y be a vector where element i is the ratio between the number of objects in cluster i and the area of ellipse i. When the cluster i is a line segment, y[i] and the density of the cluster are set to NA. Let z be the sum of all the elements of y without the NAs. Then we put shading = y/z *37 + 3. |

`clusplot.default`

for references;
`partition.object`

, `pam`

,
`pam.object`

, `clara`

,
`clara.object`

, `fanny`

,
`fanny.object`

, `par`

.

## generate 25 objects, divided into 2 clusters. x <- rbind(cbind(rnorm(10,0,0.5), rnorm(10,0,0.5)), cbind(rnorm(15,5,0.5), rnorm(15,5,0.5))) clusplot(pam(x, 2)) ## add noise, and try again : x4 <- cbind(x, rnorm(25), rnorm(25)) clusplot(pam(x4, 2))

[Package *cluster* version 1.10.2 Index]