clusteringOutput-class: container for clustering outputs in uniform structure

In MLInterfaces: Uniform interfaces to R machine learning procedures for data in Bioconductor containers

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

prcomp:

Object of class "prcompObj" a wrapped instance of stats package prcomp output

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

converter:

converter propagated from call

distFun:

distfun propagated from call

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 <[e-mail]>

Examples

showClass("clusteringOutput")

MLInterfaces documentation built on Nov. 8, 2020, 8:14 p.m.