koplsKernel {kopls} | R Documentation |
Constructs a kernel matrix K = <phi(X1
), phi(X2
)>.
The kernel function k() determines how the data is transformed and
is passed as the separate parameter Ktype
to the function.
Currently Ktype
can be either 'g' (Gaussian) or 'p' (polynomial); see the
supplied reference for definitions of these kernel functions.
koplsKernel(X1, X2, Ktype, param)
X1 |
'Left side' matrix in expression K = <phi(X1 ), phi(X2 )>. |
X2 |
'Right side' matrix in expression K = <phi(X1 ), phi(X2 )>. |
Ktype |
Type of kernel function: either 'g' (Gaussian) or 'p' (polynomial). |
param |
A vector with parameters to the kernel function. |
If the second parameter X2
is set to NULL, the kernel matrix is considered to be
symmetric and hence the kernel function can be applied at a considerable speed reduction.
This applies generally to pure training kernel or test kernels (where X1
= X2
),
but not to a hybrid test/training kernel (where X1
!= X2
).
The kernel matrix K, transformed by the kernel function specified by Ktype
.
Max Bylesjo and Mattias Rantalainen
Rantalainen M, Bylesjo M, Cloarec O, Nicholson JK, Holmes E and Trygg J. Kernel-based orthogonal projections to latent structures (K-OPLS), J Chemometrics 2007; 21:376-385. doi:10.1002/cem.1071.
data(koplsExample) ## Define kernel function parameter sigma<-25 ## Construct kernels Ktr<-koplsKernel(Xtr,NULL,'g',sigma) KteTr<-koplsKernel(Xte,Xtr,'g',sigma) KteTe<-koplsKernel(Xte,NULL,'g',sigma)