Code covered by the BSD License  

Highlights from
Modeling Lung Cancer Diagnosis Using Bayesian Network Inference

Modeling Lung Cancer Diagnosis Using Bayesian Network Inference

by

Paola Favaretto

 

03 Dec 2007 (Updated )

Pearl's message passing algorithm implementation and application to lung cancer diagnosis

bnMsgPassCreate(M, values, CPT)
function [nodes, edges] = bnMsgPassCreate(M, values, CPT)
% BNMSGPASSCREATE helper function for lungbayesdemo

% Reference: Neapolitan R., "Learning Bayesian Networks", Pearson Prentice Hall,
% Upper Saddle River, New Jersey, 2004.

%=== create a dummy structure for nodes
dummy1.id = [];      
dummy1.values = []; 
dummy1.parents = []; 
dummy1.children = [];
dummy1.peye = [];    
dummy1.lambda = [];
dummy1.CPT = [];     
dummy1.P = [];

%=== create a dummy structure for edges
dummy2.peyeX = [];
dummy2.lambdaX = [];

%=== create nodes
N = size(M,1); % number of nodes
nodes = repmat(dummy1, N, 1);

%=== create edges
edges = repmat(dummy2, size(M));

%=== populate nodes with data
for i = 1:N
    nodes(i).id = i;
    nodes(i).parents = find(M(:,i));
    nodes(i).children = find(M(i,:));
    nodes(i).CPT = CPT{i};
    nodes(i).values = values{i};
end




 

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