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Failure in initial objective function evaluation. FMINCON cannot continue.

조회 수: 4 (최근 30일)
Ankush Kumar Mishra
Ankush Kumar Mishra 2022년 2월 11일
댓글: Alan Weiss 2022년 11월 15일
Attaching my code, I am just not able to understand why this is not working. Gives the error, Failure in initial objective function evaluation. FMINCON cannot continue.
function new_hyp = max_likelihood(model)
problem.f = @(x) log_likelihood([x(1:model.nv), model.hyp(end)]',model); % calling the log likelihodd function, we maximize log likelihood the find the
% problem.f = @(x) log_likelihood( model.hyp(end)',model);
A = [];
b = [];
Aeq = [];
beq = [];
% model.hyper_bound = log([0.01, 50]); % bounds of hyperparamter
model.hyper_bound = log([0.35,2.73]); % bounds of hyperparamter
lb= model.hyper_bound(1)*ones(1,model.nv);
ub= model.hyper_bound(2)*ones(1,model.nv);
% lb = [-4.60517018598809,-4.60517018598809];
% ub = [3.91202300542815,3.91202300542815];
x0 = zeros(1,model.nv);%[0,0]; %Starting point
options = optimset('Display', 'off') ;
nonlcon=[];
new_hyp = fmincon(problem.f,x0,A,b,Aeq,beq,lb,ub,nonlcon, options)'; % compuatation of hyperparameter that maximizes the log likelihood
% new_hyp = fminsearch(problem.f,x0)';
end
function [lml] = log_likelihood(hyper_param, model)
K = model.cov_model(hyper_param, model.X(1:model.n,:), model.X(1:model.n,:)) + eye(model.n)*model.noise; % Covariance matrix using squared exponential kernel for the input points
Kchol = chol(K);
ALPHA = (Kchol\(Kchol'\model.f));
lml = model.f'*ALPHA + 2*sum(log(diag(Kchol))); % computation of log likelihood ,
end
  댓글 수: 3
Joshua Scott
Joshua Scott 2022년 11월 14일
Hey Matt,
What is the best way to test the function at x0 in matlab? (my apologies if this is a dumb question.)
Alan Weiss
Alan Weiss 2022년 11월 15일
Define your parameters hyper_param and model in your workspace. Then call
lml = log_likelihood(hyper_param, model)
Or set up your problem and x0 parameter, and call
problem.f(x0)
Alan Weiss
MATLAB mathematical toolbox documentation

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