Mercurial > hg > camir-aes2014
view toolboxes/FullBNT-1.0.7/bnt/inference/static/@quickscore_inf_engine/private/quickscore.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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function prob = quickscore(fpos, fneg, inhibit, prior, leak) % QUICKSCORE Heckerman's algorithm for BN2O networks. % prob = quickscore(fpos, fneg, inhibit, prior, leak) % % Consider a BN2O (Binary Node 2-layer Noisy-or) network such as QMR with % dieases on the top and findings on the bottom. (We assume all findings are observed, % since hidden leaves can be marginalized away.) % This algorithm takes O(2^|fpos|) time to compute the marginal on all the diseases. % % Inputs: % fpos = the positive findings (a vector of numbers in {1, ..., Nfindings}) % fneg = the negative findings (a vector of numbers in {1, ..., Nfindings}) % inhibit(i,j) = inhibition prob. for finding i, disease j, or 1.0 if j is not a parent. % prior(j) = prior prob. disease j is ON. We assume prior(off) = 1-prior(on). % leak(i) = inhibition prob. for the leak node for finding i % % Output: % prob(d) = Pr(disease d = on | ev) % % For details, see % - Heckerman, "A tractable inference algorithm for diagnosing multiple diseases", UAI89. % - 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 matlab experts, use 'mex' to compile C_quickscore, which has identical behavior to this function. [nfindings ndiseases] = size(inhibit); % make the first disease be always on, for the leak term Pon = [1 prior(:)']; Poff = 1-Pon; Uon = [leak(:) inhibit]; % U(f,d) = Pr(f=0|d=1) Uoff = [leak(:) ones(nfindings, ndiseases)]; % Uoff(f,d) = Pr(f=0|d=0) ndiseases = ndiseases + 1; npos = length(fpos); post = zeros(ndiseases, 2); % post(d,1) = alpha Pr(d=off), post(d,2) = alpha Pr(d=m) FP = length(fpos); %allbits = logical(dec2bitv(0:(2^FP - 1), FP)); allbits = logical(ind2subv(2*ones(1,FP), 1:(2^FP))-1); for si=1:2^FP bits = allbits(si,:); fprime = fpos(bits); fmask = zeros(1, nfindings); fmask(fneg)=1; fmask(fprime)=1; fmask = logical(fmask); p = 1; pterm = zeros(1, ndiseases); ptermOff = zeros(1, ndiseases); ptermOn = zeros(1, ndiseases); for d=1:ndiseases ptermOff(d) = prod(Uoff(fmask,d)); ptermOn(d) = prod(Uon(fmask,d)); pterm(d) = Poff(d)*ptermOff(d) + Pon(d)*ptermOn(d); end p = prod(pterm); sign = (-1)^(length(fprime)); for d=1:ndiseases myp = p / pterm(d); post(d,1) = post(d,1) + sign*(myp * ptermOff(d)); post(d,2) = post(d,2) + sign*(myp * ptermOn(d)); end end post(:,1) = post(:,1) .* Poff(:); post(:,2) = post(:,2) .* Pon(:); post = mk_stochastic(post); prob = post(2:end,2)'; % skip the leak term