computeProjectionFromKernel: computeProjectionFromKernel

Description Usage Arguments Value Author(s) References See Also Examples

View source: R/functions.R

Description

Compute the kernel PCA projection from an input kernel matrix.

Usage

1
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.

Author(s)

Pierrick Bruneau

References

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

See Also

computeStandardKernel

Examples

1
2
3
4

semisupKernelPCA documentation built on May 29, 2017, 8:59 p.m.