Mauch MIREX 2010

function CPD = tree_CPD(varargin)

%DTREE_CPD Make a conditional prob. distrib. which is a decision/regression tree.

%

% CPD =dtree_CPD() will create an empty tree.

if nargin==0

  % This occurs if we are trying to load an object from a file.

  CPD = init_fields;

  clamp = 0;

  CPD = class(CPD, 'tree_CPD', discrete_CPD(clamp, []));

  return;

elseif isa(varargin{1}, 'tree_CPD')

  % This might occur if we are copying an object.

  CPD = varargin{1};

  return;

end

CPD = init_fields;

clamped = 0;

fam_sz = [];

CPD = class(CPD, 'tree_CPD', discrete_CPD(clamped, fam_sz));

%%%%%%%%%%%

function CPD = init_fields()

% This ensures we define the fields in the same order 

% no matter whether we load an object from a file,

% or create it from scratch. (Matlab requires this.)

%init the decision tree set the root to null

CPD.tree.num_node = 0;

CPD.tree.root=1;

CPD.tree.nodes=[];