ControlCenter.m

%ControlCenter
OriginalData = [0 1 0 0;...
         0.1 0 0 1;...
         0.2 1 0 0;...
         0.3 1 0 0;...
         0.4 1 0 0;...
         0.4 0 1 0;...
         0.5 1 0 0;...
         0.5 0 0 1;...
         0.6 1 0 0;...
         0.6 0 0 1;...
         0.7 0 0 1;...
         0.8 0 1 0;...
         0.9 0 0 1;...
         1.0 1 0 0;...
         1.0 0 1 0;...
         1.1 0 0 1;...
         1.1 0 1 0;...
         1.1 0 1 0;...
         1.2 1 0 0;...
         1.3 1 0 0;...
         1.3 1 0 0;...
         1.3 1 0 0;...
         1.4 0 0 1;...
         1.5 0 0 1;...
         1.5 0 0 1;...
         1.6 0 0 1;...
         1.7 0 1 0;...
         1.7 0 1 0;...
         1.7 0 1 0;...
         1.8 0 0 1;...
         1.9 0 0 1;...
         2.0 0 0 1;...
         2.1 0 1 0];
% one feature variable, three class labels.
% 1. Input variables include the traget database with continuous data, named
%     as "OriginalData", the other database is the number of class variables.
% 2. Output variables include the processed database named as
%    "DiscretData", the other is "DiscretizationSet" saving the used
%    intervals.  

[ DiscretData,DiscretizationSet1 ] = CACC_Discretization( OriginalData, 3 )

% We also provide a real database 'YeastDatabase.mat' for testing, since it costs much time for
% discretization, one could delete "%" for testing. Remember to change the
% path of directory in load function. 

%load('C:\Documents and Settings\sun\My Documents\MATLAB\MBC_Database\Yeast\YeastDatabase.mat','YeastTrain'); %103 Features,14 classes, 1500 cases in  database 'YeastTrain'
%[ DiscretYeastTrain,DiscretizationSet2 ] = CACC_Discretization( YeastTrain, 14 );