| predict.credpart {evclust} | R Documentation |
Computation of a credal partition for new data
Description
predict.credpart is the predict method for "credpart"
objects generated by nnevclus or ecm.
Usage
## S3 method for class 'credpart'
predict(object, newdata, fhat = NULL, ...)
Arguments
object |
An object of class |
newdata |
A matrix of size ntest*p containing the new data. |
fhat |
An optional vector of one-class SVM outputs (for method nn-evclus only) |
... |
Additional arguments (not used). |
Details
This function computes a credal partial of newdata based on learnt information stored
in a "credpart" objects created by ecm or nnevclus.
Value
A credal partition of the new data.
References
T. Denoeux and O. Kanjanatarakul. Beyond Fuzzy, Possibilistic and Rough: An Investigation of Belief Functions in Clustering. 8th International conference on soft methods in probability and statistics, Rome, 12-14 September, 2016.
M.-H. Masson and T. Denoeux. ECM: An evidential version of the fuzzy c-means algorithm. Pattern Recognition, Vol. 41, Issue 4, pages 1384–1397, 2008.
T. Denoeux, S. Sriboonchitta and O. Kanjanatarakul. Evidential clustering of large dissimilarity data. Knowledge-Based Systems, vol. 106, pages 179-195, 2016.
See Also
Examples
## Not run:
data(fourclass)
train<-sample(400,200)
x<-fourclass[train,1:2]
x.test<-x[-train,1:2]
clus<-ecm(x,c=4,type='pairs',delta=sqrt(10),epsi=1e-3,disp=TRUE)
clus.test<-predict(clus,x.test)
plot(clus.test,x.test,mfrow=c(2,2))
## End(Not run)