手机交互网站/seo是什么级别

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麻烦各位做贝叶斯网络的朋友帮我看看。。谢谢了。

function [engine, loglik] = enter_evidence(engine, evidence, varargin)

% ENTER_EVIDENCE Add the specified evidence to the network (jtree)

% [engine, loglik] = enter_evidence(engine, evidence, ...)

%

% evidence{i} = [] if X(i) is hidden, and otherwise contains its observed value (scalar or column vector).

%

% The following optional arguments can be specified in the form of name/value pairs:

% [default value in brackets]

%

% soft - a cell array of soft/virtual evidence;

% soft{i} is a prob. distrib. over i*s values, or [] [ cell(1,N) ]

%

% e.g., engine = enter_evidence(engine, ev, *soft*, soft_ev)

bnet = bnet_from_engine(engine);

ns = bnet.node_sizes(:);

N = length(bnet.dag);

engine.evidence = evidence; % store this for marginal_nodes with add_ev option

engine.maximize = 0;

% set default params

exclude = [];

soft_evidence = cell(1,N);

% parse optional params

args = varargin;

nargs = length(args);

for i=1:2:nargs

switch args{i},

case *soft*, soft_evidence = args{i+1};

case *maximize*, engine.maximize = args{i+1};

otherwise,

error([*invalid argument name * args{i}]);

end

end

onodes = find(~isemptycell(evidence));

hnodes = find(isemptycell(evidence));

pot_type = determine_pot_type(bnet, onodes);

if strcmp(pot_type, *cg*)

check_for_cd_arcs(onodes, bnet.cnodes, bnet.dag);

end

if is_mnet(bnet)

pot = engine.user_pot;

clqs = engine.nums_ass_to_user_clqs;

else

% Evaluate CPDs with evidence, and convert to potentials

pot = cell(1, N);

for n=1:N

fam = family(bnet.dag, n);

e = bnet.equiv_class(n);

if isempty(bnet.CPD{e})

error([*must define CPD * num2str(e)])

else

pot{n} = convert_to_pot(bnet.CPD{e}, pot_type, fam(:), evidence);

end

end

clqs = engine.clq_ass_to_node(1:N);

end

% soft evidence

soft_nodes = find(~isemptycell(soft_evidence));

S = length(soft_nodes);

if S > 0

assert(pot_type == *d*);

assert(mysubset(soft_nodes, bnet.dnodes));

end

for i=1:S

n = soft_nodes(i);

pot{end+1} = dpot(n, ns(n), soft_evidence{n});

end

clqs = [clqs engine.clq_ass_to_node(soft_nodes)];

[clpot, seppot] = init_pot(engine, clqs, pot, pot_type, onodes);

[clpot, seppot] = collect_evidence(engine, clpot, seppot);

[clpot, seppot] = distribute_evidence(engine, clpot, seppot);

C = length(clpot);

ll = zeros(1, C);

for i=1:C

[clpot{i}, ll(i)] = normalize_pot(clpot{i});

end

loglik = ll(1); % we can extract the likelihood from any clique

engine.clpot = clpot;