1

我正在尝试从 fminsearch 优化返回结果。我正在使用 fminsearch 来查找 SVM 的最佳超参数（变量 z）。匿名函数正在最小化分类错误（'Crit'），但我也希望返回在同一迭代中获得的另一个变量（给定超参数的选定特征）（'Features'）：

fun = @(z)SVM_min_fn(Data,Labels,exp(z(1)),exp(z(2)),num_folds);
[z_opt,Crit] = fminsearch(fun,z0,opts);

function [Crit Features] = SVM_min_fn(Data,Labels,rbf_sigma,boxconstraint,num_folds)
direction = 'forward';
opts = statset('display','iter');
kernel = 'rbf';

disp(sprintf('RBF sigma: %1.4f. Boxconstraint: %1.4f',rbf_sigma,boxconstraint))
c = cvpartition(Labels,'k',num_folds);
opts = statset('display','iter','TolFun',1e-3);
fun = @(x_train,y_train,x_test,y_test)SVM_class_fun(x_train,y_train,x_test,y_test,kernel,rbf_sigma,boxconstraint);
[fs,history] = sequentialfs(fun,Data,Labels,'cv',c,'direction',direction,'options',opts);

Features = find(fs==1);        % Features selected for given sigma and C
[Crit,h] = min(history.Crit);  % Mean classification error

有没有办法让“fminsearch”同时返回“Crit”和Features？保存到工作区不起作用，因为功能不是“fminsearch”返回的超参数的正确功能

4

1 回答 1

3

如果您在完成后再进行一次函数评估，这是最简单的fminsearch：

fun = @(z)SVM_min_fn(Data,Labels,exp(z(1)),exp(z(2)),num_folds);
[z_opt,Crit] = fminsearch(fun,z0,opts);

[~, Features_opt] = fun(z_opt);
于 2012-09-25T11:22:01.550 回答