finish mushroom

booster/tree/xgboost_svdf_tree.hpp

@@ -544,7 +544,11 @@ namespace xgboost{
                                "input data smaller than num feature" );
                 int pid = this->GetLeafIndex( feat, funknown, gid );
                 return tree[ pid ].leaf_value();
-            }        
+            }
+            
+            virtual void DumpModel( FILE *fo ){
+                tree.DumpModel( fo );
+            }
         public:
             RTreeTrainer( void ){ silent = 0; }
             virtual ~RTreeTrainer( void ){}

booster/tree/xgboost_tree_model.h

@@ -284,6 +284,26 @@ namespace xgboost{
             inline int num_extra_nodes( void ) const {
                 return param.num_nodes - param.num_roots - param.num_deleted;
             }
+            /*! \brief dump model to text file  */
+            inline void DumpModel( FILE *fo ){
+                this->Dump( 0, fo, 0 );
+            }
+        private:
+            void Dump( int nid, FILE *fo, int depth ){
+                for( int  i = 0;  i < depth; ++ i ){
+                    fprintf( fo, "\t" );
+                }
+                if( nodes[ nid ].is_leaf() ){
+                    fprintf( fo, "%d:leaf=%f\n", nid, nodes[ nid ].leaf_value() );
+                }else{
+                    // right then left,
+                    TSplitCond cond = nodes[ nid ].split_cond();
+                    fprintf( fo, "%d:[f%u>%f] yes=%d,no=%d\n", nid, 
+                             nodes[ nid ].split_index(), float(cond), nodes[ nid ].cright(), nodes[ nid ].cleft() );
+                    this->Dump( nodes[ nid ].cright(), fo, depth+1 );
+                    this->Dump( nodes[ nid ].cleft(), fo, depth+1 );
+                }                
+            } 
         };
     };
 

booster/xgboost.h

@@ -92,6 +92,13 @@ namespace xgboost{
              * \param fo output stream 
              */        
             virtual void PrintInfo( FILE *fo ){}
+            /*! 
+             * \brief dump model into text file
+             * \param fo output stream 
+             */        
+            virtual void DumpModel( FILE *fo ){
+                utils::Error( "not implemented" );                
+            }
         public:
             /*! \brief virtual destructor */
             virtual ~IBooster( void ){}

booster/xgboost_gbmbase.h

@@ -169,6 +169,16 @@ namespace xgboost{
                     this->ConfigBooster( this->boosters[i] );
                 }
             }
+            /*! 
+             * \brief DumpModel
+             * \param fo text file 
+             */            
+            inline void DumpModel( FILE *fo ){
+                for( size_t i = 0; i < boosters.size(); i ++ ){
+                    fprintf( fo, "booster[%d]\n", (int)i );
+                    boosters[i]->DumpModel( fo );
+                }
+            }
         public:
             /*! 
              * \brief do gradient boost training for one step, using the information given

demo/mushroom/maptree.py

@@ -0,0 +1,21 @@
+#!/usr/bin/python
+import sys
+
+def loadnmap( fname ):
+    nmap = {}
+    for l in open(fname):
+        arr = l.split()
+        nmap[int(arr[0])] = arr[1].strip()
+    return nmap
+
+fo = sys.stdout
+nmap = loadnmap( 'featname.txt' )
+for l in open( 'dump.txt'):
+    idx = l.find('[f')
+    if idx == -1:
+        fo.write(l)
+    else:
+        fid = int( l[idx+2:len(l)].split('>')[0])
+        rl = l[0:idx]+'['+nmap[fid]+']' + l.split()[1].strip()+'\n'
+        fo.write(rl)
+

demo/mushroom/runexp.sh

@@ -2,3 +2,5 @@
 python mapfeat.py
 python mknfold.py agaricus.txt 1
 ../../xgboost mushroom.conf
+../../xgboost mushroom.conf task=dump model_in=0003.model
+python maptree.py

regression/xgboost_reg.h

@@ -89,16 +89,23 @@ namespace xgboost{
             * \param fi input stream
             */          
             inline void LoadModel( utils::IStream &fi ){
-                utils::Assert( fi.Read( &mparam, sizeof(ModelParam) ) != 0 );
                 base_model.LoadModel( fi );
+                utils::Assert( fi.Read( &mparam, sizeof(ModelParam) ) != 0 );
+            }
+            /*! 
+             * \brief DumpModel
+             * \param fo text file 
+             */            
+            inline void DumpModel( FILE *fo ){
+                base_model.DumpModel( fo );
             }
             /*! 
             * \brief save model to stream
             * \param fo output stream
             */
             inline void SaveModel( utils::IStream &fo ) const{
-                fo.Write( &mparam, sizeof(ModelParam) );
                 base_model.SaveModel( fo );	
+                fo.Write( &mparam, sizeof(ModelParam) );
             } 
             /*! 
              * \brief update the model for one iteration

regression/xgboost_reg_main.cpp

@@ -34,6 +34,10 @@ namespace xgboost{
                 }
                 this->InitData();
                 this->InitLearner();
+                if( !strcmp( task.c_str(), "dump") ){
+                    this->TaskDump();
+                    return 0;
+                }
                 if( !strcmp( task.c_str(), "test") ){
                     this->TaskTest();
                 }else{
@@ -68,6 +72,7 @@ namespace xgboost{
                 task = "train";                
                 model_in = "NULL";
                 name_pred = "pred.txt";
+                name_dump = "dump.txt";
                 model_dir_path = "./";
             }
             ~RegBoostTask( void ){
@@ -77,6 +82,7 @@ namespace xgboost{
             }
         private:
             inline void InitData( void ){
+                if( !strcmp( task.c_str(), "dump") ) return;
                 if( !strcmp( task.c_str(), "test") ){
                     data.CacheLoad( test_path.c_str() );
                 }else{
@@ -126,6 +132,12 @@ namespace xgboost{
                     printf("\nupdating end, %lu sec in all\n", elapsed );
                 }
             }
+
+            inline void TaskDump( void ){
+                FILE *fo = utils::FopenCheck( name_dump.c_str(), "w" );
+                learner.DumpModel( fo );
+                fclose( fo );
+            }
             inline void SaveModel( int i ) const{
                 char fname[256];
                 sprintf( fname ,"%s/%04d.model", model_dir_path.c_str(), i+1 );
@@ -161,6 +173,8 @@ namespace xgboost{
             std::string task;
             /* \brief name of predict file */
             std::string name_pred;
+            /* \brief name of dump file */
+            std::string name_dump;
             /* \brief the paths of validation data sets */
             std::vector<std::string> eval_data_paths;            
             /* \brief the names of the evaluation data used in output log */