Home > Mateda2.0 > knowledge_extraction > BN_Fitness_Corr.m

# BN_Fitness_Corr

## PURPOSE

[bn_fit_corr] = BN_Fitness_Corr(bnet,Pop,FunVal):

## SYNOPSIS

function[bn_fit_corr] = BN_Fitness_Corr(bnet,Pop,FunVal)

## DESCRIPTION

     [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)

## CROSS-REFERENCE INFORMATION

This function calls:

- BN_Pop_Prob [Prob] = BN_Pop_Prob(bnet,Pop):

This function is called by:

- BN_Prediction EXAMPLE 2: Evaluation of the prediction capability of the models
- Find_Fitness_Approx [Func_Models] = Find_Fitness_Approx(AllModels,ParetoPop,ParetoVals)

## SOURCE CODE

    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