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📄 gaussian_cpd_params_given_dps.m

📁 贝叶斯算法(matlab编写) 安装,添加目录 /home/ai2/murphyk/matlab/FullBNT
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function [m, C, W] = gaussian_CPD_params_given_dps(CPD, domain, evidence)% GAUSSIAN_CPD_PARAMS_GIVEN_EV_ON_DPS Extract parameters given evidence on all discrete parents% function [m, C, W] = gaussian_CPD_params_given_ev_on_dps(CPD, domain, evidence)ps = domain(1:end-1);dps = ps(CPD.dps);if isempty(dps)  m = CPD.mean;  C = CPD.cov;  W = CPD.weights;else  odom = domain(~isemptycell(evidence(domain)));  dops = myintersect(dps, odom);  dpvals = cat(1, evidence{dops});  if length(dops) == length(dps)    dpsizes = CPD.sizes(CPD.dps);    dpval = subv2ind(dpsizes, dpvals(:)');    m = CPD.mean(:, dpval);    C = CPD.cov(:, :, dpval);    W = CPD.weights(:, :, dpval);  else    map = find_equiv_posns(dops, dps);    index = mk_multi_index(length(dps), map, dpvals);    m = CPD.mean(:, index{:});    C = CPD.cov(:, :, index{:});    W = CPD.weights(:, :, index{:});  endend

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