Merge branch 'master' of https://github.com/tqchen/xgboost
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README.md
12
README.md
@ -3,8 +3,8 @@ xgboost: eXtreme Gradient Boosting
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An efficient general purpose gradient boosting (tree) library.
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Creater: Tianqi Chen
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Documentation: https://github.com/tqchen/xgboost/wiki
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Turorial and Documentation: https://github.com/tqchen/xgboost/wiki
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Features
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@ -15,7 +15,7 @@ Features
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- Efficient implementation that optimizes memory and computation.
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* Layout of gradient boosting algorithm to support generic tasks, see project wiki.
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Planned key components
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Supported key components
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=======
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* Gradient boosting models:
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- regression tree (GBRT)
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@ -23,10 +23,14 @@ Planned key components
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* Objectives to support tasks:
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- regression
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- classification
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* OpenMP implementation
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Planned components
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=======
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* More objective to support tasks:
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- ranking
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- matrix factorization
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- structured prediction
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(3) OpenMP implementation
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File extension convention:
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(1) .h are interface, utils and data structures, with detailed comment;
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@ -4,23 +4,20 @@ python mapfeat.py
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# split train and test
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python mknfold.py agaricus.txt 1
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# training
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../../xgboost mushroom.conf num_round=1 model_out=full.model bst:max_depth=3
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../../xgboost mushroom.conf num_round=2 model_out=full.model bst:max_depth=3
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../../xgboost mushroom.conf task=dump model_in=full.model fmap=featmap.txt name_dump=dump.full.txt
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# constrain
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../../xgboost mushroom.conf num_round=1 model_out=ban.model bst:max_depth=3 bst:fban=22-31
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# major element of batch running: add batch prefix to each setting, batch:run=1 will run that action
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# constrain
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../../xgboost mushroom.conf num_round=1 model_out=pass.model bst:max_depth=3 bst:fdefault=-1 bst:fpass=22-31
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../../xgboost mushroom.conf model_in=full.model model_out=m1.model task=interact\
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batch:interact:booster_index=0 batch:bst:interact:remove=1 batch:run=1\
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batch:interact:booster_index=1 batch:bst:interact:remove=1 batch:run=1\
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batch:interact:booster_index=1 batch:bst:interact:expand=9 batch:run=1\
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../../xgboost mushroom.conf task=dump model_in=ban.model fmap=featmap.txt name_dump=dump.ban.txt
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../../xgboost mushroom.conf task=dump model_in=pass.model fmap=featmap.txt name_dump=dump.pass.txt
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../../xgboost mushroom.conf task=dump model_in=m1.model fmap=featmap.txt name_dump=dump.m1.txt
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echo "========full======="
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cat dump.full.txt
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echo "========ban======="
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cat dump.ban.txt
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echo "========pass======="
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cat dump.pass.txt
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echo "========m1======="
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cat dump.m1.txt
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@ -73,6 +73,9 @@ namespace xgboost{
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if( !strcmp("name_pred", name ) ) name_pred = val;
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if( !strcmp("dump_stats", name ) ) dump_model_stats = atoi( val );
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if( !strcmp("interact:action", name ) ) interact_action = val;
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if( !strncmp("batch:", name, 6 ) ){
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cfg_batch.PushBack( name + 6, val );
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}
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if( !strncmp("eval[", name, 5 ) ) {
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char evname[ 256 ];
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utils::Assert( sscanf( name, "eval[%[^]]", evname ) == 1, "must specify evaluation name for display");
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@ -167,13 +170,27 @@ namespace xgboost{
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inline void TaskInteractive( void ){
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const time_t start = time( NULL );
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unsigned long elapsed = 0;
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learner.UpdateInteract( interact_action );
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int batch_action = 0;
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cfg_batch.BeforeFirst();
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while( cfg_batch.Next() ){
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if( !strcmp( cfg_batch.name(), "run" ) ){
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learner.UpdateInteract( interact_action );
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batch_action += 1;
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} else{
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learner.SetParam( cfg_batch.name(), cfg_batch.val() );
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}
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}
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if( batch_action == 0 ){
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learner.UpdateInteract( interact_action );
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}
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utils::Assert( model_out != "NULL", "interactive mode must specify model_out" );
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this->SaveModel( model_out.c_str() );
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elapsed = (unsigned long)(time(NULL) - start);
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if( !silent ){
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printf("\ninteractive update, %lu sec in all\n", elapsed );
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printf("\ninteractive update, %d batch actions, %lu sec in all\n", batch_action, elapsed );
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}
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}
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@ -245,6 +262,8 @@ namespace xgboost{
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std::vector<std::string> eval_data_names;
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/*! \brief saves configurations */
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utils::ConfigSaver cfg;
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/*! \brief batch configurations */
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utils::ConfigSaver cfg_batch;
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private:
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DMatrix data;
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std::vector<DMatrix*> deval;
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