BN_Fitness_Corr

 [bn_fit_corr] =  BN_Fitness_Corr(bnet,Pop,FunVal):   
 BN_Fitness_Corr:          Computes the correlation between the probabilities given to the solutions by the
                           networks and the fitness values of the  solutions
 INPUTS 
 bnet:                Bayesian network
 Pop:                 Population
 FunVal:             Evaluation vector for each of the objectives
 OUTPUTS
 bn_fit_corr: Vector of correlations for each of the objectives.

 Last version 8/26/2008. Roberto Santana (roberto.santana@ehu.es)

0001 function[bn_fit_corr] =  BN_Fitness_Corr(bnet,Pop,FunVal)
0002 % [bn_fit_corr] =  BN_Fitness_Corr(bnet,Pop,FunVal):
0003 % BN_Fitness_Corr:          Computes the correlation between the probabilities given to the solutions by the
0004 %                           networks and the fitness values of the  solutions
0005 % INPUTS
0006 % bnet:                Bayesian network
0007 % Pop:                 Population
0008 % FunVal:             Evaluation vector for each of the objectives
0009 % OUTPUTS
0010 % bn_fit_corr: Vector of correlations for each of the objectives.
0011 %
0012 % Last version 8/26/2008. Roberto Santana (roberto.santana@ehu.es)
0013 
0014 
0015  [Prob] =  BN_Pop_Prob(bnet,Pop);
0016  
0017  number_objectives = size(FunVal,2);
0018  
0019  for i=1:number_objectives,
0020   bn_fit_corr(i) = corr(Prob,FunVal(:,i));
0021  end,
0022  
0023 
0024  
0025