R: Assign clusters to new data

Assign clusters to new data

Usage

predict.cclust(clobj, x)

Arguments

`clobj`	Object returned by a clustering algorithm such as `cclust`
`x`	Data matrix

Description

Assigns each data point (row in x) the cluster corresponding to the closest center found in clobj.

Value

predict.cclust returns an object of class "cclust". Only size is changed as compared to the argument clobj.

`cluster`	Vector containing the indices of the clusters where the data is mapped.
`size`	The number of data points in each cluster.

Author(s)

Friedrich Leisch and Andreas Weingessel

Examples

# a 2-dimensional example
x<-rbind(matrix(rnorm(100,sd=0.3),ncol=2),
         matrix(rnorm(100,mean=1,sd=0.3),ncol=2))
cl<-cclust(x,2,20,verbose=TRUE,method="kmeans")
plot(cl,x)   

# a 3-dimensional example
x<-rbind(matrix(rnorm(150,sd=0.3),ncol=3),
         matrix(rnorm(150,mean=1,sd=0.3),ncol=3),
         matrix(rnorm(150,mean=2,sd=0.3),ncol=3))
cl<-cclust(x,6,20,verbose=TRUE,method="kmeans")
plot(cl,x)

# assign classes to some new data
y<-rbind(matrix(rnorm(33,sd=0.3),ncol=3),
         matrix(rnorm(33,mean=1,sd=0.3),ncol=3),
         matrix(rnorm(3,mean=2,sd=0.3),ncol=3))
ycl<-predict(cl, y)
plot(cl,y)

[Package Contents]