semisupKernelPCA (version 0.1.4)

computeStandardKernel: computeStandardKernel

Description

Compute a kernel matrix from a data set.

Usage

computeStandardKernel(data, pgaussian=TRUE)

Arguments

data

n x d matrix of d-dimensional row-elements.

pgaussian

if TRUE, use the p-gaussian kernel function (see Francois et al. 2005). Else use the classic gaussian kernel, ie p-gaussian function with p=2 and sigma set to the maximal pairwise distance between elements of the data set.

Value

• n x n kernel matrix.

References

Francois, D., Wertz, V. and Verleysen, M. (2005) About the locality of kernels in high-dimensional spaces. International Symposium on Applied Stochastic Models and Data Analysis. 238-245.

See Also

computeCompositeKernel

Examples

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