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D2L2R2_top.m
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D2L2R2_top.m
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function best_acc = D2L2R2_top(dataset, N_train, k, lambda1, lambda2, alpha)
% function D2L2R2_top(dataset, N_train, k, lambda1, lambda2, alpha)
% * The top function of D2L2R2
% * INPUT:
% + `dataset`: name of the dataset stored in `.mat` file in `data` folder.
% Note that `dataset` is the file name of the `.mat`, excluding `.mat`.
% + `N_train`: number of training samples in each class
% + `k`: number of atoms in EACH dictionary
% + `lambda1, lambda2, alpha`: regularization parameters.
% * To run an small example, type `D2L2r2-top` without input in MATLAB
% command window.
% -----------------------------------------------
% Author: Tiep Vu, thv102@psu.edu, 5/13/2016 10:29:48 PM
% (http://www.personal.psu.edu/thv102/)
% -----------------------------------------------
addpath(genpath('utils'));
addpath('ODL');
addpath('LRSDL_FDDL');
addpath('D2L2R2');
%% test mode
if nargin == 0
dataset = 'myYaleB';
N_train = 10;
k = 8;
lambda1 = 0.001;
lambda2 = 0.01;
alpha = 0.01;
end
%% Data preparation
t = getTimeStr();
[dataset, Y_train, Y_test, label_train, label_test] = train_test_split(...
dataset, N_train);
%% main
[acc, rt] = D2L2R2_wrapper(Y_train, label_train, Y_test, label_test,...
k, lambda1, lambda2, alpha);
%% save results
if ~exist('results', 'dir')
mkdir('results');
end
if ~exist(fullfile('results', 'D2L2R2'), 'dir')
mkdir('results', 'D2L2R2');
end
fn = fullfile('results', 'D2L2R2', strcat(dataset, '_N_', ...
num2str(N_train), '_k_', num2str(k), '_l1_', num2str(lambda1),...
'_l2_', num2str(lambda2), '_a_', num2str(alpha), '_', t, '.mat'));
disp(fn);
save(fn, 'acc', 'rt');
best_acc = max(acc);
end