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]