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- filters = {'Associative Memory','None','Perceptron'};
- act_funcs = {'Hardlim', 'Linear' ,'Sigmoidal'};
- learningstyles = {'Batch'};
- %learningstyles = {'Incremental'};
- %learningfunc = {'gradient rule', 'gradient rule improved with momentum', 'hebb rule' ,'hebb rule with decaying weight', 'Widrow-Hoff learning rule'};
- %
- learningfunc = {'gradient descent','gradient descent with adaptive learning rate','gradient with moment','Levenberg-Marquardt','scaled conjugate gradient'};
- AP = load('P.mat');
- P = AP.P;
- result = [];
- for filter = filters
- for f = act_funcs
- for style = learningstyles
- for func = learningfunc
- result = [result ; coach(P,filter{1},f{1},style{1},func{1})];
- end
- end
- end
- end
- cell2csv('data.csv',result)
- function cell2csv(filename,cellArray,delimiter)
- % Writes cell array content into a *.csv file.
- %
- % CELL2CSV(filename,cellArray,delimiter)
- %
- % filename = Name of the file to save. [ i.e. 'text.csv' ]
- % cellarray = Name of the Cell Array where the data is in
- % delimiter = seperating sign, normally:',' (default)
- %
- % by Sylvain Fiedler, KA, 2004
- % modified by Rob Kohr, Rutgers, 2005 - changed to english and fixed delimiter
- if nargin<3
- delimiter = ',';
- end
- datei = fopen(filename,'w');
- for z=1:size(cellArray,1)
- for s=1:size(cellArray,2)
- var = eval(['cellArray{z,s}']);
- if size(var,1) == 0
- var = '';
- end
- if isnumeric(var) == 1
- var = num2str(var);
- end
- fprintf(datei,var);
- if s ~= size(cellArray,2)
- fprintf(datei,[delimiter]);
- end
- end
- fprintf(datei,'\n');
- end
- fclose(datei);
- end
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