buzzun
2018-05-24, 17:10
bnet=mk_bnet(DAG,node_sizes);
seed = 0;
rand('state',seed);
for i=1:N
bnet.CPD{i} = tabular_CPD(bnet,i);
end
bnet2=learn_params(bnet,Sample);
CPT1=cell(1,N)
for i=i:N
s=struct(bnet.CPD{i});
CPT1{i}=s.CPT;
end
??? Error using ==> run
Index exceeds matrix dimensions.
贝叶斯网络用k2算法已经生成,10个节点,2048个case,每个节点有两个取值,1,0.,这里的N=10,node_sizes={2,2,2,2,2,2,2,2,2,2}
seed = 0;
rand('state',seed);
for i=1:N
bnet.CPD{i} = tabular_CPD(bnet,i);
end
bnet2=learn_params(bnet,Sample);
CPT1=cell(1,N)
for i=i:N
s=struct(bnet.CPD{i});
CPT1{i}=s.CPT;
end
??? Error using ==> run
Index exceeds matrix dimensions.
贝叶斯网络用k2算法已经生成,10个节点,2048个case,每个节点有两个取值,1,0.,这里的N=10,node_sizes={2,2,2,2,2,2,2,2,2,2}