Mercurial > hg > camir-aes2014
diff toolboxes/FullBNT-1.0.7/bnt/inference/static/@belprop_inf_engine/find_mpe.m @ 0:e9a9cd732c1e tip
first hg version after svn
author | wolffd |
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date | Tue, 10 Feb 2015 15:05:51 +0000 |
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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/toolboxes/FullBNT-1.0.7/bnt/inference/static/@belprop_inf_engine/find_mpe.m Tue Feb 10 15:05:51 2015 +0000 @@ -0,0 +1,49 @@ +function mpe = find_mpe(engine, evidence, varargin) +% FIND_MPE Find the most probable explanation of the data (belprop) +% function mpe = find_mpe(engine, evidence,...) +% +% evidence{i} = [] if X(i) is hidden, and otherwise contains its observed value (scalar or column vector). +% +% This finds the marginally most likely value for each hidden node, +% and may give the wrong results even if the graph is acyclic, +% unless you set break_ties = 1. +% +% The following optional arguments can be specified in the form of name/value pairs: +% [default value in brackets] +% +% break_ties is optional. If 1, we will force ties to be broken consistently +% by calling enter_evidence N times. (see Jensen96, p106) Default = 1. + +break_ties = 1; + +% parse optional params +args = varargin; +nargs = length(args); +for i=1:2:nargs + switch args{i}, + case 'break_ties', break_ties = args{i+1}; + otherwise, + error(['invalid argument name ' args{i}]); + end +end + +engine = enter_evidence(engine, evidence, 'maximize', 1); + +observed = ~isemptycell(evidence); +evidence = evidence(:); % hack to handle unrolled DBNs +N = length(evidence); +mpe = cell(1,N); +for i=1:N + m = marginal_nodes(engine, i); + % observed nodes are all set to 1 inside the inference engine, so we must undo this + if observed(i) + mpe{i} = evidence{i}; + else + mpe{i} = argmax(m.T); + if break_ties + evidence{i} = mpe{i}; + [engine, ll] = enter_evidence(engine, evidence, 'maximize', 1); + end + end +end +