| predict.cclust {cclust} | R Documentation |
Assigns each data point (row in x) the cluster corresponding to
the closest center found in y.
predict(y, x)
y |
Object of class "cclust" returned by a clustering algorithm such as cclust |
x |
Data matrix where columns correspond to variables and rows to observations |
predict.cclust returns an object of class "cclust".
Only size is changed as compared to the argument
y.
cluster |
Vector containing the indices of the clusters where the data is mapped. |
size |
The number of data points in each cluster. |
Friedrich Leisch and Andreas Weingessel
# 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(ycl,y)