KERNEL |
Evaluates kernel function.
Synopsis:
K = kernel(X,ker,arg)
K = kernel(X1,X2,ker,arg)
Description:
K = kernel( X, ker, arg ) returns kernel matrix K [n x n]
K(i,j) = k(X(:,i),X(:,j)) for all i=1..n, j=1..n,
where k: a x b -> R is a kernel function given by
identifier ker and argument arg:
Identifier Name Definition
'linear' ... linear kernel k(a,b) = a'*b
'poly' ... polynomial k(a,b) = (a'*b+arg[2])^arg[1]
'rbf' ... RBF (Gaussian) k(a,b) = exp(-0.5*||a-b||^2/arg[1]^2)
'sigmoid' ... Sigmoidal k(a,b) = tanh(arg[1]*(a'*b)+arg[2])
K = kernel( X1, X2, ker, arg ) returns kernel matrix K [n1 x n2]
K(i,j) = k(X1(:,i),X2(:,j)) for all i=1..n1, j=1..n2,
Input:
X [dim x n] Single matrix of input vectors.
X1 [dim x n1], X2 [dim x n2] Pair of input matrices.
ker [string] Kernel identifier.
arg [1 x narg] Kernel argument.
Output:
K [n1 x n1] or K [n1 x n2] Kernel matrix.
Example:
X = rand(2,50);
K = kernel( X, 'rbf', 1);
figure; pcolor( K );
See also:
DIAGKER, KERNELPROJ.
About: Statistical Pattern Recognition Toolbox
(C) 1999-2003, Written by Vojtech Franc and Vaclav Hlavac
Czech Technical University Prague
Faculty of Electrical Engineering
Center for Machine Perception
Modifications:
19-sep-2004, VF
5-may-2004, VF