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This commit is contained in:
tqchen
2014-03-05 15:28:53 -08:00
parent 2bdcad9630
commit ef5a389ecf
7 changed files with 142 additions and 24 deletions
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70
booster/tree/xgboost_row_treemaker.hpp
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@@ -30,6 +30,17 @@ namespace xgboost{
utils::Assert( grad.size() == hess.size(), "booster:invalid input" );
utils::Assert( smat.NumRow() == hess.size(), "booster:invalid input" );
utils::Assert( root_index.size() == 0 || root_index.size() == hess.size(), "booster:invalid input" );
{// setup temp space for each thread
if( param.nthread != 0 ){
omp_set_num_threads( param.nthread );
}
#pragma omp parallel
{
this->nthread = omp_get_num_threads();
}
tmp_rptr.resize( this->nthread, std::vector<size_t>() );
snode.reserve( 256 );
}
}
inline void Make( int& stat_max_depth, int& stat_num_pruned ){
this->InitData();
@@ -51,7 +62,38 @@ namespace xgboost{
}
// start prunning the tree
stat_num_pruned = this->DoPrune();
}
}
// expand a specific node
inline bool Expand( const std::vector<bst_uint> &valid_index, int nid ){
if( valid_index.size() == 0 ) return false;
this->InitDataExpand( valid_index, nid );
this->InitNewNode( this->qexpand );
this->FindSplit( nid, tmp_rptr[0] );
// update node statistics
for( size_t i = 0; i < qexpand.size(); ++ i ){
const int nid = qexpand[i];
tree.stat( nid ).loss_chg = snode[ nid ].best.loss_chg;
tree.stat( nid ).sum_hess = static_cast<float>( snode[ nid ].sum_hess );
}
// change the leaf
this->UpdateQueueExpand( this->qexpand );
this->InitNewNode( this->qexpand );
// set all the rest expanding nodes to leaf
for( size_t i = 0; i < qexpand.size(); ++ i ){
const int nid = qexpand[i];
tree[ nid ].set_leaf( snode[nid].weight * param.learning_rate );
tree.stat( nid ).loss_chg = 0.0f;
tree.stat( nid ).sum_hess = static_cast<float>( snode[ nid ].sum_hess );
tree.param.max_depth = std::max( tree.param.max_depth, tree.GetDepth( nid ) );
}
if( qexpand.size() != 0 ) {
return true;
}else{
return false;
}
}
private:
// make leaf nodes for all qexpand, update node statistics, mark leaf value
inline void InitNewNode( const std::vector<int> &qexpand ){
@@ -71,9 +113,11 @@ namespace xgboost{
snode[nid].root_gain = param.CalcRootGain( sum_grad, sum_hess );
if( !tree[nid].is_root() ){
snode[nid].weight = param.CalcWeight( sum_grad, sum_hess, snode[ tree[nid].parent() ].weight );
snode[nid].weight = param.CalcWeight( sum_grad, sum_hess, tree.stat( tree[nid].parent() ).base_weight );
tree.stat(nid).base_weight = snode[nid].weight;
}else{
snode[nid].weight = param.CalcWeight( sum_grad, sum_hess, 0.0f );
tree.stat(nid).base_weight = snode[nid].weight;
}
}
}
@@ -288,18 +332,7 @@ namespace xgboost{
node_bound[i-1] = std::make_pair( rptr[ i - 1 ], rptr[ i ] );
}
}
{// setup temp space for each thread
if( param.nthread != 0 ){
omp_set_num_threads( param.nthread );
}
#pragma omp parallel
{
this->nthread = omp_get_num_threads();
}
tmp_rptr.resize( this->nthread, std::vector<size_t>() );
snode.reserve( 256 );
}
{// expand query
qexpand.reserve( 256 ); qexpand.clear();
for( int i = 0; i < tree.param.num_roots; ++ i ){
@@ -307,6 +340,15 @@ namespace xgboost{
}
}
}
// initialize temp data structure
inline void InitDataExpand( const std::vector<bst_uint> &valid_index, int nid ){
row_index_set = valid_index;
node_bound.resize( tree.param.num_nodes );
node_bound[ nid ] = std::make_pair( 0, (bst_uint)row_index_set.size() );
qexpand.clear(); qexpand.push_back( nid );
}
private:
// number of omp thread used during training
int nthread;