comparison toolboxes/FullBNT-1.0.7/bnt/inference/static/@quickscore_inf_engine/quickscore_inf_engine.m @ 0:e9a9cd732c1e tip

first hg version after svn

+function engine = quickscore_inf_engine(inhibit, leak, prior)
+% QUICKSCORE_INF_ENGINE Exact inference for the QMR network
+% engine = quickscore_inf_engine(inhibit, leak, prior)
+%
+% We create an inference engine for QMR-like networks.
+% QMR is a bipartite graph, where the top layer contains hidden disease nodes,
+% and the bottom later contains observed finding nodes.
+% The diseases have Bernoulli CPDs, the findings noisy-or CPDs.
+% The original QMR (Quick Medical Reference) network has specific parameter values which we are not
+% allowed to release, for commercial reasons.
+%
+% inhibit(f,d) = inhibition probability on f->d arc for disease d, finding f
+% If inhibit(f,d) = 1, there is effectively no arc from d->f
+% leak(j) = inhibition prob. on leak node -> finding j arc
+% prior(i) = prob. disease i is on
+%
+% We use exact inference, which takes O(2^P) time, where P is the number of positive findings.
+% For details, see
+% - Heckerman, "A tractable inference algorithm for diagnosing multiple diseases", UAI 89.
+% - Rish and Dechter, "On the impact of causal independence", UCI tech report, 1998.
+% Note that this algorithm is numerically unstable, since it adds a large number of positive and
+% negative terms and hopes that some of them exactly cancel.
+%
+% For an interesting variational approximation, see
+% - Jaakkola and Jordan, "Variational probabilistic inference and the QMR-DT network", JAIR 10, 1999.
+%
+% See also 
+% - "Loopy belief propagation for approximate inference: an empirical study",
+%      K. Murphy, Y. Weiss and M. Jordan, UAI 99.
+
+engine.inhibit = inhibit;
+engine.leak = leak;
+engine.prior = prior;
+
+% store results here between enter_evidence and marginal_nodes
+engine.post = [];
+
+engine = class(engine, 'quickscore_inf_engine'); % not a child of the inf_engine class!