kpca-class {kernlab} | R Documentation |
The Kernel Principal Components Analysis class
Objects can be created by calls of the form new("kpca", ...)
.
or by calling the kpca
function.
pcv
:"matrix"
containing the
principal component vectors eig
:"vector"
containing the
coresponding eigenvaluesrotated
:"matrix"
containing the
projection of the data on the principal componentskernelf
:"function"
containing
the kernel function usedkpar
:"list"
containing the
kernel parameters used xmatrix
:"matrix"
conatining
the data matrix used kcall
:"ANY"
containing the
function call n.action
:"ANY"
containg the
action performed on NA signature(object = "kpca")
: returns the eigenvalues signature(object = "kpca")
: returns the
performed callsignature(object = "kpca")
: returns the used
kernel functionsignature(object = "kpca")
: returns the principal
component vectors signature(object = "kpca")
: embeeds new data signature(object = "kpca")
: returns the
projected datasignature(object = "kpca")
: returns the used
data matrix
Alexandros Karatzoglou
alexandros.karatzoglou@ci.tuwien.ac.at
# another example using the iris data(iris) test <- sample(1:50,20) kpc <- kpca(~.,data=iris[-test,-5],kernel="rbfdot",kpar=list(sigma=0.2),features=2) #print the principal component vectors pcv(kpc) rotated(kpc) kernelf(kpc) eig(kpc)