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readData.m
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readData.m
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function [data,varNames,varTypes] = readFile(filePath)
% This function reads experiment data from .csv file with n columns
%
% The .csv file has to be structured as follows
% Column 1 to n-1 = attributes
% Last column = variable to be predicted
%
% 1st row = name of attributes and variable to be predicted
% 2nd row = attribute and variable types (0 = Real, 1 = Categorical)
% remaining rows = the data samples
%
%
%
% Copyright 2015 Riccardo Taormina (riccardo_taormina@sutd.edu.sg),
% Gulsah Karakaya (gulsahkilickarakaya@gmail.com;),
% Stefano Galelli (stefano_galelli@sutd.edu.sg),
% and Selin Damla Ahipasaoglu (ahipasaoglu@sutd.edu.sg;.
%
% Please refer to README.txt for further information.
%
%
% This file is part of Matlab-Multi-objective-Feature-Selection.
%
% Matlab-Multi-objective-Feature-Selection is free software: you can redistribute
% it and/or modify it under the terms of the GNU General Public License
% as published by the Free Software Foundation, either version 3 of the
% License, or (at your option) any later version.
%
% This code is distributed in the hope that it will be useful,
% but WITHOUT ANY WARRANTY; without even the implied warranty of
% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
% GNU General Public License for more details.
%
% You should have received a copy of the GNU General Public License
% along with MATLAB_IterativeInputSelection.
% If not, see <http://www.gnu.org/licenses/>.
%
% load file using xlsread
[temp_a,temp_b] = xlsread(filePath);
% extract attribute and variable types
varTypes = temp_a(1,:);
% extract data samples
data = temp_a(2:end,:);
% get names
varNames = temp_b(1,:);