clusteringOutput-class {MLInterfaces} | R Documentation

## container for clustering outputs in uniform structure

### Description

container for clustering outputs in uniform structure

### Objects from the Class

Objects can be created by calls of the form `new("clusteringOutput", ...)`.

### Slots

`partition`:
  Object of class `"integer"`, labels for observations as clustered
`silhouette`:
  Object of class `"silhouette"`, structure from Rousseeuw cluster package measuring cluster membership strength per observation
`distEnv`:
  Object of class `"environment"` not in use
`prcomp`:
  Object of class `"prcompObj"` a wrapped instance of stats package prcomp output
`metric`:
  Object of class `"character"` string identifying the distance function used to orient objects in feature space
`call`:
  Object of class `"call"` for auditing
`learnerSchema`:
  Object of class `"learnerSchema"`, a formal object indicating the package, function, and other attributes of the clustering algorithm employed to generate this object
`RObject`:
  Object of class `"ANY"`, the unaltered output of the function called according to learnerSchema

### Methods

RObject
  `signature(x = "clusteringOutput")`: extract the unaltered output of the R function or method called according to learnerSchema
plot
  `signature(x = "clusteringOutput", y = "ANY")`: a 4-panel plot showing features of the clustering, including the scree plot for a principal components transformation and a display of the partition in PC1xPC2 plane. For a clustering method that does not have a native plot procedure, such as kmeans, the parameter y should be bound to a data frame or matrix with feature data for all records; an image plot of robust feature z-scores (z=(x-median(x))/mad(x)) and the cluster indices is produced in the northwest panel.
show
  `signature(object = "clusteringOutput")`: concise report

### Author(s)

VJ Carey <stvjc@channing.harvard.edu>

### Examples

    showClass("clusteringOutput")

[Package MLInterfaces version 1.22.0 Index]