Mercurial > hg > scatter_reeval
view dss/classification/classify.m @ 0:503d0475274e
Version 0.0.1 - Initial Commit
author | Francisco Rodriguez Algarra <f.rodriguezalgarra@qmul.ac.uk> |
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date | Wed, 21 Oct 2015 00:02:11 +0100 |
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function [] = classify(db, optt, preffix) cond = cellstr(['none '; 'fault']); for ii=1:length(cond) [train_set,test_set] = createFolds(cond{ii}); train_set = find(train_set)'; test_set = find(test_set)'; [dev_err_grid,C_grid,gamma_grid] = ... svm_adaptive_param_search(db,train_set,[],optt); [dev_err,ind] = min(mean(dev_err_grid{end},2)); C = C_grid{end}(ind); gamma = gamma_grid{end}(ind); optt1 = optt; optt1.C = C; optt1.gamma = gamma; model = svm_train(db,train_set,optt1); labels = svm_test(db,model,test_set); err = classif_err(labels,test_set,db.src); fprintf('dev err = %f, test err = %f\n\n',dev_err,err); % dummy renaming of variables id = test_set'; true_label = kron((1:10), ones(1, 100)); true_label = true_label(test_set)'; pred_label = labels'; % saving results in table results = table(id, true_label, pred_label) run_name = [preffix, cond{ii}]; global results_dir; [s, mess, messid] = mkdir(results_dir); if(s ~= 1) exit; end; save([results_dir, run_name, '.mat'],'dev_err','err','C','gamma', 'labels', 'results'); writetable(results, [results_dir, run_name, '_results.csv']) end;