predict.cclust {cclust}

Assign clusters to new data

Description

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

Usage

## S3 method for class 'cclust'
predict(object, newdata, ...)

Arguments

object

Object of class "cclust" returned by a clustering algorithm such as cclust

newdata

Data matrix where columns correspond to variables and rows to observations

...

currently not used

Value

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

cluster

Vector containing the indices of the clusters where the data is mapped.

size

The number of data points in each cluster.

Author(s)

Evgenia Dimitriadou

See Also

cclust

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(x, col=cl$cluster)   

# 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(x, col=cl$cluster)

# 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(y, col=ycl$cluster)