berek_evidence_gamma_gradr.m

The goal of SPID is to provide the user with tools capable to simulate, preprocess, process and clas

function [resultaat, gradient] = berek_evidence_gamma_gradR(gam)


gam = abs(gam)+100*eps; gam
global sigm kern Xtr Ytr KK roK ALFA BETA EW ED EffPar;

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% Start  LEVEL 1 OPTIMISATION
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N = size(Xtr,1);
lssvm_aoptions('eps', 0.0000000000001);
lssvm_aoptions('deltaphi', 0.00000000000001);
lssvm_aoptions('maxiter', 200);
lssvm_aoptions('sigma', sigm);
lssvm_aoptions('kerneltype', kern);
lssvm_aoptions('show', 0);
lssvm_aoptions('memoryintensive', 1);
lssvm_aoptions('gamma', (gam));
[alfa_lssvm, b_lssvm, aux] = lssvm_atrain(Xtr,Ytr);
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Stop  LEVEL 1 OPTIMISATION
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Calculate LEVEL 2 cost function + gradient
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ek = 1/gam*alfa_lssvm;
Ed = 1/2*sum(ek.^2);
Ew = 1/2*sum(alfa_lssvm.*(Ytr-ek-b_lssvm));

Neff = length(roK); 
som_log = sum(log(roK*gam+1)) - (N-1)*log(gam);

resultaat = som_log + (N-1)*log(Ew+gam*Ed);

gradient =  sum(roK./(roK*gam+1)) - (N-1)/(gam) + (N-1)/(Ew+gam*Ed)*Ed;

% Doe output naar de rest
ALFA = (N-1)/(2*(Ew+gam*Ed) );
BETA = gam*ALFA;
ED = Ed;
EW = Ew;