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kernlab (version 0.9-24)

kpca-class: Class "kpca"

Description

The Kernel Principal Components Analysis class

Arguments

Objects of class "kpca"

Objects can be created by calls of the form new("kpca", ...). or by calling the kpca function.

Slots

pcv:
Object of class "matrix" containing the principal component vectors
eig:
Object of class "vector" containing the corresponding eigenvalues
rotated:
Object of class "matrix" containing the projection of the data on the principal components
kernelf:
Object of class "function" containing the kernel function used
kpar:
Object of class "list" containing the kernel parameters used
xmatrix:
Object of class "matrix" containing the data matrix used
kcall:
Object of class "ANY" containing the function call
n.action:
Object of class "ANY" containing the action performed on NA

Methods

eig
signature(object = "kpca"): returns the eigenvalues
kcall
signature(object = "kpca"): returns the performed call
kernelf
signature(object = "kpca"): returns the used kernel function
pcv
signature(object = "kpca"): returns the principal component vectors
predict
signature(object = "kpca"): embeds new data
rotated
signature(object = "kpca"): returns the projected data
xmatrix
signature(object = "kpca"): returns the used data matrix

See Also

ksvm-class, kcca-class

Examples

Run this code
# 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)

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