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1 function fh=hme_reg_plot(net, nodes_info, train_data, test_data)
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2 %
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3 % Use this function ONLY when the input dimension is 1
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4 % and the problem is a regression one.
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5 % We assume that each row of 'train_data' & 'test_data' is an example.
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6 %
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7 % ----------------------------------------------------------------------------------------------------
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8 % -> pierpaolo_b@hotmail.com or -> pampo@interfree.it
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9 % ----------------------------------------------------------------------------------------------------
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10
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11 fh=figure('Name','HME based regression', 'MenuBar', 'none', 'NumberTitle', 'off');
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12
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13 mn_x_train = round(min(train_data(:,1)));
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14 mx_x_train = round(max(train_data(:,1)));
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15 x_train = mn_x_train(1):0.01:mx_x_train(1);
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16 Z_train=fhme(net, nodes_info, x_train',size(x_train,2)); % forward propagation trougth the HME
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17
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18 if nargin==4,
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19 subplot(2,1,1);
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20 mn_x_test = round(min(test_data(:,1)));
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21 mx_x_test = round(max(test_data(:,1)));
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22 x_test = mn_x_test(1):0.01:mx_x_test(1);
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23 Z_test=fhme(net, nodes_info, x_test',size(x_test,2)); % forward propagation trougth the HME
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24 end
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25
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26 hold on;
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27 set(gca, 'Box', 'on');
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28 plot(x_train', Z_train, 'r');
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29 plot(train_data(:,1),train_data(:,2),'+k');
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30 title('Training set and prediction');
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31 hold off
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32
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33 if nargin==4,
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34 subplot(2,1,2);
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35 hold on;
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36 set(gca, 'Box', 'on');
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37 plot(x_train', Z_train, 'r');
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38 if size(test_data,2)==2,
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39 plot(test_data(:,1),test_data(:,2),'+k');
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40 end
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41 title('Test set and prediction');
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42 hold off
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43 end |
