fs_unsup_udfs_single_func.m

function [FeaNumCandi,res_gs,res_aio, res_gs_ps] = fs_unsup_udfs_single_func(dataset, exp_settings, algo_settings)
% run UDFS feature selection algorithm

%======================setup===========================
FeaNumCandi = exp_settings.FeaNumCandi;
nKmeans = exp_settings.nKmeans;
prefix_mdcs = [];
if isfield(exp_settings, 'prefix_mdcs')
    prefix_mdcs = exp_settings.prefix_mdcs;
end
%======================================================

disp(['dataset:',dataset]);
[X, Y] = extractXY(dataset);
[nSmp, nDim] = size(X);
nClass = length(unique(Y));

%======================setup===========================
gammaCandi = 10.^(-5:5);
lamdaCandi = 10.^(-5:5);
knnCandi = 5;
paramCell = fs_unsup_udfs_build_param(knnCandi, gammaCandi, lamdaCandi);
%======================================================

t_start = clock;
disp('UDFS ...');
feaSubsets = cell(length(paramCell), 1);
parfor i1 = 1:length(paramCell)
    fprintf('UDFS parameter search %d out of %d...\n', i1, length(paramCell));
    param = paramCell{i1};
    L = LocalDisAna(X', param);
    A = X'*L*X;
    W = fs_unsup_udfs(A, nClass, param.gamma);
    [~, idx] = sort(sum(W.*W,2),'descend');
    feaSubsets{i1,1} = idx;
end
t_end = clock;
t1 = etime(t_end,t_start);
disp(['exe time: ',num2str(t1)]);

t_start = clock;
disp('evaluation ...');
res_aio = cell(length(paramCell), length(FeaNumCandi));
for i2 = 1:length(FeaNumCandi)
    m = FeaNumCandi(i2);
    parfor i1 = 1:length(paramCell)
        fprintf('UDFS parameter evaluation %d outof %d  ... %d out of %d...\n', i2, length(FeaNumCandi), i1, length(paramCell));
        idx = feaSubsets{i1,1};
        res_aio{i1, i2} = evalUnSupFS(X, Y, idx(1:m), struct('nKm', nKmeans));
    end
end
[res_gs, res_gs_ps] = grid_search_fs(res_aio);
res_gs.feaset = FeaNumCandi;
t_end = clock;
t2 = etime(t_end,t_start);
disp(['exe time: ',num2str(t2)]);
res_gs.time = t1;
res_gs.time2 = t2;

save(fullfile(prefix_mdcs, [dataset, '_best_result_UDFS.mat']),'FeaNumCandi','res_gs','res_aio', 'res_gs_ps');
end