Home > Mateda2.0 > knowledge_extraction > BN_Pop_Prob.m

# BN_Pop_Prob

## PURPOSE

[Prob] = BN_Pop_Prob(bnet,Pop):

## SYNOPSIS

function[Prob] = BN_Pop_Prob(bnet,Pop)

## DESCRIPTION

     [Prob] =  BN_Pop_Prob(bnet,Pop):
     BN_Pop_Prob:      Computes the probabilities given to the solutions in Pop by the
                       networks
     INPUTS
     bnet:                Bayesian network
     Pop:                 Population
     OUTPUTS
     Prob: Vector with the probabilities given by Bayesian network to each of
     the solutions

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

## CROSS-REFERENCE INFORMATION

This function calls:

This function is called by:

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

## SOURCE CODE

    0001 function[Prob] =  BN_Pop_Prob(bnet,Pop)
    0002 % [Prob] =  BN_Pop_Prob(bnet,Pop):
    0003 % BN_Pop_Prob:      Computes the probabilities given to the solutions in Pop by the
    0004 %                   networks
    0005 % INPUTS
    0006 % bnet:                Bayesian network
    0007 % Pop:                 Population
    0008 % OUTPUTS
    0009 % Prob: Vector with the probabilities given by Bayesian network to each of
    0010 % the solutions
    0011 %
    0012 % Last version 8/26/2008. Roberto Santana (roberto.santana@ehu.es)
    0013
    0014 PopSize = size(Pop,1);
    0015
    0016 engine = jtree_inf_engine(bnet, 'maximize', 1);
    0017
    0018  for i=1:PopSize,
    0019    vect = num2cell(Pop(i,:)+1);
    0020    [eng, logprob] = enter_evidence(engine,vect);
    0021    Prob(i,1) = exp(logprob);
    0022  end