convert_to_pot.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 45 行
M
45 行
function pot = convert_to_pot(CPD, pot_type, domain, evidence)
% CONVERT_TO_POT Convert a tabular CPD to one or more potentials
% pots = convert_to_pot(CPD, pot_type, domain, evidence)
%
% pots{i} = CPD evaluated using evidence(domain(:,i))
% If 'domains' is a single row vector, pots will be an object, not a cell array.
ncases = size(domain,2);
assert(ncases==1); % not yet vectorized
sz = dom_sizes(CPD);
ns = zeros(1, max(domain));
ns(domain) = sz;
local_ev = evidence(domain);
obs_bitv = ~isemptycell(local_ev);
odom = domain(obs_bitv);
T = convert_to_table(CPD, domain, local_ev, obs_bitv);
switch pot_type
case 'u',
pot = upot(domain, sz, T, 0*myones(sz));
case 'd',
ns(odom) = 1;
pot = dpot(domain, ns(domain), T);
case {'c','g'},
% Since we want the output to be a Gaussian, the whole family must be observed.
% In other words, the potential is really just a constant.
p = T;
%p = prob_node(CPD, evidence(domain(end)), evidence(domain(1:end-1)));
ns(domain) = 0;
pot = cpot(domain, ns(domain), log(p));
case 'cg',
T = T(:);
ns(odom) = 1;
can = cell(1, length(T));
for i=1:length(T)
can{i} = cpot([], [], log(T(i)));
end
pot = cgpot(domain, [], ns, can);
otherwise,
error(['unrecognized pot type ' pot_type])
end
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