dbs-class: Class "dbs"

In pdfCluster: Cluster Analysis via Nonparametric Density Estimation

Class "dbs"

Description

This class pertains to results of the application of function dbs.

Objects from the Class

Objects can be created by calls of the form new("dbs", ...) or as a result from calling function dbs.

Slots

call:

Object of class "call" reporting the matched call.

x:

Object of class "matrix" representing the clustered data points.

prior:

Object of class "numeric" being the prior probabilities of belonging to the groups.

dbs:

Object of class "numeric" reporting the density-based silhouette information of the clustered data.

clusters:

Object of class "numeric" reporting the group labels of grouped data.

noc:

Object of class "numeric" indicating the number of clusters.

stage:

Object of class "ANY" corresponding to the stage of the classification at which the density-based silhouette information is computed when dbs is applied to an object of pdfCluster-class.

Methods

plot

signature(x = "dbs", y = "missing"):

S4 method for plotting objects of dbs-class. Data are partitioned into the clusters, sorted in a decreasing order with respect to their dbs value and displayed on a bar graph. See plot,dbs-method for further details.

show

signature(object = "dbs"):

S4 method for showing objects of dbs-class. The following elements are shown:

• the dbs index computed at the observed data;

• The cluster membership of each data point;

summary

signature(object = "dbs"):

S4 method for summarizing objects of dbs-class. The following elements are shown:

• a summary (minimum, 1st quartile, median, mean, 3rd quartile, maximum) of the dbs values for each cluster;

• a summary (minimum, 1st quartile, median, mean, 3rd quartile, maximum) of the dbs values for all the observations.

See Also

dbs, silhouette, plot,dbs-method, plot-methods, show-methods, summary-methods.

Examples

showClass("dbs")

#wine example
#data loading
data(wine)

# select a subset of variables
x <- wine[, c(2,5,8)]

#clustering
cl <- pdfCluster(x)
 
dsil <- dbs(cl)
dsil
summary(dsil)

pdfCluster documentation built on Dec. 2, 2022, 5:14 p.m.