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show_spec_v_modes

PURPOSE ^

SHOW_SPEC_V_MODES: Shows the specificity of the models versus

SYNOPSIS ^

function [mean_specs, std_specs] = show_spec_v_modes(models, training_data, n_iters, ref_points_vec)

DESCRIPTION ^

 SHOW_SPEC_V_MODES: Shows the specificity of the models versus
                    the difference of modes.

 Code written by Katherine Smith, 2003

    GENERAL

      [mean_specs, std_specs] = show_spec_v_modes
             (models, training_data, n_iters, ref_points_vec)

    INPUT/S

      -models:
           The models to be investigated.

      -training_data:
           The training data that is used with the model.

      -n_iters:
           Number of iteration used to control complexity.

      -ref_points_vec:
           The points of the reference image
           
    OUTPUT/S

      -mean_specs:
           Mean specificity.

      -std_specs:
           Standard deviation of specificity.

    PENDING WORK

      -

    KNOWN BUG/S

      -None.

    COMMENT/S

      -

    RELATED FUNCTION/S

      

    ABOUT

      -Created:     November 23rd, 2003
      -Last update: Novermber 27th, 2003
      -Revision:    0.0.3
      -Author:      R. S. Schestowitz, University of Manchester
 ==============================================================

CROSS-REFERENCE INFORMATION ^

This function calls: This function is called by:

SOURCE CODE ^

0001 function [mean_specs, std_specs] = show_spec_v_modes(models, training_data, n_iters, ref_points_vec)
0002 % SHOW_SPEC_V_MODES: Shows the specificity of the models versus
0003 %                    the difference of modes.
0004 %
0005 % Code written by Katherine Smith, 2003
0006 %
0007 %    GENERAL
0008 %
0009 %      [mean_specs, std_specs] = show_spec_v_modes
0010 %             (models, training_data, n_iters, ref_points_vec)
0011 %
0012 %    INPUT/S
0013 %
0014 %      -models:
0015 %           The models to be investigated.
0016 %
0017 %      -training_data:
0018 %           The training data that is used with the model.
0019 %
0020 %      -n_iters:
0021 %           Number of iteration used to control complexity.
0022 %
0023 %      -ref_points_vec:
0024 %           The points of the reference image
0025 %
0026 %    OUTPUT/S
0027 %
0028 %      -mean_specs:
0029 %           Mean specificity.
0030 %
0031 %      -std_specs:
0032 %           Standard deviation of specificity.
0033 %
0034 %    PENDING WORK
0035 %
0036 %      -
0037 %
0038 %    KNOWN BUG/S
0039 %
0040 %      -None.
0041 %
0042 %    COMMENT/S
0043 %
0044 %      -
0045 %
0046 %    RELATED FUNCTION/S
0047 %
0048 %
0049 %
0050 %    ABOUT
0051 %
0052 %      -Created:     November 23rd, 2003
0053 %      -Last update: Novermber 27th, 2003
0054 %      -Revision:    0.0.3
0055 %      -Author:      R. S. Schestowitz, University of Manchester
0056 % ==============================================================
0057 
0058 n_models = size(models,1); 
0059            % retrieve number of models
0060 
0061 for i = 1:n_models
0062            % for each model
0063   n_modes = size(models(i).model.pcs,2); 
0064            % get number of modes in the current model
0065   for j=1:n_modes
0066            % calculate specificity using index j modes
0067     [mean_spec(i,j), std_spec(i,j)]= find_specificity(models(i).model,training_data, n_iters, ref_points_vec, 'n_modes', j);
0068   end
0069 end
0070 
0071 mean_specs = mean(mean_spec);
0072            % get the overall mean
0073 std_specs = mean(std_spec);
0074            % get the overall mean

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