Assign clusters to new data
Assigns each data point (row in newdata) the cluster corresponding to
the closest center found in object.
## S3 method for class 'cclust' predict(object, newdata, ...)
object |
Object of class |
newdata |
Data matrix where columns correspond to variables and rows to observations |
... |
currently not used |
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. |
Evgenia Dimitriadou
# 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)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.