semisupKernelPCA (version 0.1.5)

computeProjectionFromKernel: computeProjectionFromKernel

Description

Compute the kernel PCA projection from an input kernel matrix.

Usage

computeProjectionFromKernel(kernel, dims=2, eigentype=c("basic", "irlba"))

Arguments

kernel

n x n kernel matrix

dims

number of output dimensions for the projection. Cannot exceed n.

eigentype

Indicates the eigendecomposition routine that should be used, either the standard ("basic"), or an optimization for the extraction of a few major eigenpairs ("irlba")

Value

• n x dims matrix of the projected data.

References

Bishop, C. M. (2006) Pattern recognition and machine learning. Springer.

See Also

computeStandardKernel

Examples

data(iris)
irisdat <- as.matrix(iris[,1:4])
kernel <- computeKernel(irisdat)
proj <- computeProjectionFromKernel(kernel)