void CMlStaticStructLearn::CreateResultBNet(CDAG* pDAG)
{
int i, j, k, ns;
int nnodes = m_nNodes;
CDAG* iDAG = pDAG->TopologicalCreateDAG(m_vResultRenaming);
nodeTypeVector vnt;
m_pGrModel->GetNodeTypes(&vnt);
intVector na(nnodes);
const int* nas = m_pGrModel->GetNodeAssociations();
for(i=0; i<nnodes; i++) na[i] = nas[m_vResultRenaming[i]];
m_pResultBNet = CBNet::Create(nnodes, vnt.size(), &vnt.front(),
&na.front(), static_cast<CGraph*>(iDAG));
const CNodeType* nt;
int nEv = m_Vector_pEvidences.size();
CEvidence** pEv = new CEvidence*[nEv];
intVector obsnodes(nnodes);
for(i=0; i<nnodes; i++) obsnodes[i] = i;
valueVector new_data;
const Value* val;
for(i = 0 ; i < nEv; i++)
{
for(j=0; j<nnodes; j++)
{
val = m_Vector_pEvidences[i]->GetValue(m_vResultRenaming[j]);
nt = m_pResultBNet->GetNodeType(j);
if(nt->IsDiscrete())
{
new_data.push_back(*val);
}
else
{
ns = nt->GetNodeSize();
for(k=0; k<ns; k++)
new_data.push_back(*(val+k));
}
}
pEv[i] = CEvidence::Create(m_pResultBNet, nnodes, &obsnodes.front(), new_data);
new_data.clear();
}
vnt.clear();
intVector vFamily;
m_pResultBNet->AllocFactors();
for(i=0; i<nnodes; i++)
{
vFamily.clear();
iDAG->GetParents(i, &vFamily);
vFamily.push_back(i);
CCPD* iCPD = ComputeFactor(vFamily, m_pResultBNet, pEv);
m_pResultBNet->AttachFactor(iCPD);
}
for(i=0; i<nEv; i++)delete pEv[i];
delete[] pEv;
}
void CMlStaticStructLearnHC::LearnInOneStart(CDAG* InitDag,
CDAG** LearnedDag, float* LearnedScore)
{
int i, j, step=0;
bool progress = true;
CDAG* iDAG = InitDag->Clone();
floatVector FamilyScore;
float init_score = ScoreDAG(iDAG, &FamilyScore);
int nValidMoves;
EDGEOPVECTOR vValidMoves;
EDGEOP move;
intVector newFamily;
intVector vAncestor, vDescent;
intVector vDiscrete, vContinuous;
int start, end, position;
const CNodeType* nt;
for(i=0; i<m_nNodes; i++)
{
nt = m_pGrModel->GetNodeType(i);
if( nt->IsDiscrete() )
vDiscrete.push_back(i);
else
vContinuous.push_back(i);
}
vAncestor.assign(m_vAncestor.begin(), m_vAncestor.end());
vDescent.assign(m_vDescent.begin(), m_vDescent.end());
while ( step<m_nSteps && progress )
{
iDAG->GetAllValidMove(&vValidMoves,&vDiscrete, &vContinuous, &vDescent, &vAncestor);
nValidMoves = vValidMoves.size();
float tmp_score, max_score = 0.0f;
float tmp_start, max_start = 0.0f;
float tmp_end, max_end = 0.0f;
int max_index = 0;
for(i=0; i<nValidMoves; i++)
{
newFamily.clear();
move = vValidMoves[i];
switch (move.DAGChangeType)
{
case DAG_DEL :
start = move.originalEdge.startNode;
end = move.originalEdge.endNode;
iDAG->GetParents(end, &newFamily);
newFamily.push_back(end);
position = std::find(newFamily.begin(), newFamily.end(), start)
- newFamily.begin();
newFamily.erase(newFamily.begin()+position);
tmp_score = ScoreFamily(newFamily) - FamilyScore[end];
if(tmp_score > max_score)
{
max_score = tmp_score;
max_index = i;
}
break;
case DAG_ADD :
start = move.originalEdge.startNode;
end = move.originalEdge.endNode;
iDAG->GetParents(end, &newFamily);
position = newFamily.size();
for(j=0; j<newFamily.size(); j++)
{
if(start<newFamily[j])
{
position = j;
break;
}
}
if(position == int(newFamily.size()))
newFamily.push_back(start);
else
newFamily.insert(newFamily.begin()+position, start);
newFamily.push_back(end);
if(newFamily.size() > (m_nMaxFanIn+1))
break;
tmp_score = ScoreFamily(newFamily) - FamilyScore[end];
if(tmp_score > max_score)
{
max_score = tmp_score;
max_index = i;
}
break;
case DAG_REV :
start = move.originalEdge.startNode;
end = move.originalEdge.endNode;
iDAG->GetParents(start, &newFamily); //add an edge
position = newFamily.size();
for(j=0; j<newFamily.size(); j++)
{
if(end<newFamily[j])
{
position = j;
break;
}
}
if(position == int(newFamily.size()))
newFamily.push_back(end);
else
newFamily.insert(newFamily.begin()+position, end);
newFamily.push_back(start);
if(newFamily.size() > (m_nMaxFanIn+1))
break;
tmp_score = ScoreFamily(newFamily) - FamilyScore[start];
tmp_start = tmp_score;
start = move.originalEdge.startNode;
end = move.originalEdge.endNode;
iDAG->GetParents(end, &newFamily);
newFamily.push_back(end);
position = std::find(newFamily.begin(), newFamily.end(), start)
- newFamily.begin();
newFamily.erase(newFamily.begin()+position);
tmp_score = ScoreFamily(newFamily) - FamilyScore[end];
tmp_end = tmp_score;
tmp_score = tmp_start + tmp_end;
if(tmp_score > max_score)
{
max_score = tmp_score;
max_start = tmp_start;
max_end = tmp_end;
max_index = i;
}
break;
}
}
float score_gate = (float)fabs(m_minProgress * init_score);
if(max_score <= score_gate)
{
vValidMoves.clear();
progress = false;
break;
}
move = vValidMoves[max_index];
start = move.originalEdge.startNode;
end = move.originalEdge.endNode;
switch (move.DAGChangeType)
{
case DAG_DEL :
if(iDAG->DoMove(start, end, DAG_DEL))
{
init_score += max_score;
FamilyScore[end] += max_score;
}
break;
case DAG_ADD :
if(iDAG->DoMove(start, end, DAG_ADD))
{
init_score += max_score;
FamilyScore[end] += max_score;
}
break;
case DAG_REV :
if(iDAG->DoMove(start, end, DAG_REV))
{
init_score += max_score;
FamilyScore[start] += max_start;
FamilyScore[end] += max_end;
}
break;
}
vValidMoves.clear();
step++;
}
*LearnedScore = this->ScoreDAG(iDAG, &FamilyScore);
*LearnedDag = iDAG->Clone();
delete iDAG;
}