enter_evidence.m

来自「贝叶斯网络的matlab实现。可以创建贝叶斯网络、训练模型」· M 代码 · 共 44 行

function [engine, loglik] = enter_evidence(engine, evidence, varargin)
% ENTER_EVIDENCE Add the specified evidence to the network (jtree_unrolled_dbn)
% [engine, loglik] = enter_evidence(engine, evidence, ...)
%
% evidence{i,t} = [] if if X(i,t) is hidden, and otherwise contains its observed value (scalar or column vector)
% 
% The following optional arguments can be specified in the form of name/value pairs:
% [default value in brackets]
%
% maximize - if 1, does max-product instead of sum-product [0]
% filter   - if 1, does filtering (not supported), else smoothing [0]
%
% e.g., engine = enter_evidence(engine, ev, 'maximize', 1)

maximize = 0;
filter = 0;

% parse optional params
args = varargin;
nargs = length(args);
if nargs > 0
  for i=1:2:nargs
    switch args{i},
     case 'maximize', maximize = args{i+1}; 
     case 'filter',  filter = args{i+1}; 
     otherwise,  
      error(['invalid argument name ' args{i}]);       
    end
  end
end

if filter
  error('jtree_unrolled_dbn does not support filtering')
end

if size(evidence,2) ~= engine.nslices
  error(['engine was created assuming there are ' num2str(engine.nslices) ...
	 ' slices, but evidence has ' num2str(size(evidence,2))])
end

[engine.unrolled_engine, loglik] = enter_evidence(engine.unrolled_engine, evidence, 'maximize', maximize);