Home > batch > prt_cfg_cv_model.m

prt_cfg_cv_model

PURPOSE ^

Preprocessing of the data.

SYNOPSIS ^

function cv_model = prt_cfg_cv_model

DESCRIPTION ^

 Preprocessing of the data.
_______________________________________________________________________
 Copyright (C) 2011 Machine Learning & Neuroimaging Laboratory

CROSS-REFERENCE INFORMATION ^

This function calls: This function is called by:

SUBFUNCTIONS ^

SOURCE CODE ^

0001 function cv_model = prt_cfg_cv_model
0002 % Preprocessing of the data.
0003 %_______________________________________________________________________
0004 % Copyright (C) 2011 Machine Learning & Neuroimaging Laboratory
0005 
0006 % Written by A. Marquand
0007 % $Id$
0008 
0009 % ---------------------------------------------------------------------
0010 % filename Filename(s) of data
0011 % ---------------------------------------------------------------------
0012 infile        = cfg_files;
0013 infile.tag    = 'infile';
0014 infile.name   = 'Load PRT.mat';
0015 infile.filter = 'mat';
0016 infile.num    = [1 1];
0017 infile.help   = {'Select PRT.mat (file containing data/design structure).'};
0018 
0019 % ---------------------------------------------------------------------
0020 % model_name Feature set name
0021 % ---------------------------------------------------------------------
0022 model_name         = cfg_entry;
0023 model_name.tag     = 'model_name';
0024 model_name.name    = 'Model name';
0025 model_name.help    = {'Name of a model. Must match your entry in the '...
0026                       '''Specify model'' batch module.'};
0027 model_name.strtype = 's';
0028 model_name.num     = [1 Inf];
0029 
0030 % ---------------------------------------------------------------------
0031 % no_perm No permutation test
0032 % ---------------------------------------------------------------------
0033 no_perm         = cfg_const;
0034 no_perm.tag     = 'no_perm';
0035 no_perm.name    = 'No permutation test';
0036 no_perm.val     = {1};
0037 no_perm.help    = {'Do not perform permutation test'};
0038 
0039 % ---------------------------------------------------------------------
0040 % N_perm Number of permutations
0041 % ---------------------------------------------------------------------
0042 N_perm         = cfg_entry;
0043 N_perm.tag     = 'N_perm';
0044 N_perm.name    = 'Number of permutations';
0045 N_perm.help    = {'Enter the number of permutations to perform'};
0046 N_perm.strtype = 'e';
0047 N_perm.val     = {1000};
0048 N_perm.num     = [1 1];
0049 
0050 % ---------------------------------------------------------------------
0051 % flag_sw Save the permutations' weights
0052 % ---------------------------------------------------------------------
0053 flag_sw         = cfg_menu;
0054 flag_sw.tag     = 'flag_sw';
0055 flag_sw.name    = 'Save permutations parameters';
0056 flag_sw.help    = {['Set to Yes to save the parameterss obtained from each' ...
0057     'permutation.']};
0058 flag_sw.labels  = {
0059                'Yes'
0060                'No'
0061 }';
0062 flag_sw.values  = {1 0};
0063 flag_sw.val     = {0};
0064 
0065 % ---------------------------------------------------------------------
0066 % perm_t Do permuatation test
0067 % ---------------------------------------------------------------------
0068 perm_t         = cfg_branch;
0069 perm_t.tag     = 'perm_t';
0070 perm_t.name    = 'Permutation test';
0071 perm_t.val     = {N_perm, flag_sw};
0072 perm_t.help    = {'Perform a permutation test.'};
0073 
0074 % ---------------------------------------------------------------------
0075 % detrend Conditions
0076 % ---------------------------------------------------------------------
0077 perm_test        = cfg_choice;
0078 perm_test.tag    = 'perm_test';
0079 perm_test.name   = 'Do permutation test?';
0080 perm_test.values = {no_perm, perm_t};
0081 perm_test.val    = {no_perm};
0082 perm_test.help   = {'Perform a permutation test on accuracy, or not'};
0083 
0084 % ---------------------------------------------------------------------
0085 % cv_model Preprocessing
0086 % ---------------------------------------------------------------------
0087 cv_model        = cfg_exbranch;
0088 cv_model.tag    = 'cv_model';
0089 cv_model.name   = 'Run model';
0090 cv_model.val    = {infile model_name perm_test};
0091 cv_model.help   = {...
0092     ['Trains and tests the predictive machine using the cross-validation ',...
0093      'structure specified by the model.']};
0094 cv_model.prog   = @prt_run_cv_model;
0095 cv_model.vout   = @vout_data;
0096 
0097 %------------------------------------------------------------------------
0098 %% Output function
0099 %------------------------------------------------------------------------
0100 function cdep = vout_data(job)
0101 % Specifies the output from this modules, i.e. the filename of the mat file
0102 
0103 cdep(1)            = cfg_dep;
0104 cdep(1).sname      = 'PRT.mat file';
0105 cdep(1).src_output = substruct('.','files');
0106 cdep(1).tgt_spec   = cfg_findspec({{'filter','mat','strtype','e'}});
0107 %------------------------------------------------------------------------

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