Daniel@0: function fh=hme_reg_plot(net, nodes_info, train_data, test_data)
Daniel@0: % 
Daniel@0: % Use this function ONLY when the input dimension is 1
Daniel@0: % and the problem is a regression one.
Daniel@0: % We assume that each row of 'train_data' & 'test_data' is an example.
Daniel@0: %
Daniel@0: % ----------------------------------------------------------------------------------------------------
Daniel@0: % -> pierpaolo_b@hotmail.com   or   -> pampo@interfree.it
Daniel@0: % ----------------------------------------------------------------------------------------------------
Daniel@0: 
Daniel@0: fh=figure('Name','HME based regression', 'MenuBar', 'none', 'NumberTitle', 'off');
Daniel@0: 
Daniel@0: mn_x_train = round(min(train_data(:,1)));
Daniel@0: mx_x_train = round(max(train_data(:,1)));     
Daniel@0: x_train = mn_x_train(1):0.01:mx_x_train(1);
Daniel@0: Z_train=fhme(net, nodes_info, x_train',size(x_train,2));      % forward propagation trougth the HME
Daniel@0: 
Daniel@0: if nargin==4,
Daniel@0:     subplot(2,1,1);
Daniel@0:     mn_x_test = round(min(test_data(:,1)));
Daniel@0:     mx_x_test = round(max(test_data(:,1)));
Daniel@0:     x_test = mn_x_test(1):0.01:mx_x_test(1);
Daniel@0:     Z_test=fhme(net, nodes_info, x_test',size(x_test,2));      % forward propagation trougth the HME
Daniel@0: end
Daniel@0: 
Daniel@0: hold on;
Daniel@0: set(gca, 'Box', 'on');
Daniel@0: plot(x_train', Z_train, 'r');
Daniel@0: plot(train_data(:,1),train_data(:,2),'+k');
Daniel@0: title('Training set and prediction');
Daniel@0: hold off
Daniel@0: 
Daniel@0: if nargin==4,
Daniel@0:     subplot(2,1,2);
Daniel@0:     hold on;
Daniel@0:     set(gca, 'Box', 'on');
Daniel@0:     plot(x_train', Z_train, 'r');
Daniel@0:     if size(test_data,2)==2,
Daniel@0:         plot(test_data(:,1),test_data(:,2),'+k');
Daniel@0:     end
Daniel@0:     title('Test set and prediction');
Daniel@0:     hold off
Daniel@0: end