add regression data
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tqchen
parent
51a63d80d0
commit
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@ -78,6 +78,13 @@ namespace xgboost{
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inline size_t NumRow( void ) const{
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inline size_t NumRow( void ) const{
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return row_ptr.size() - 1;
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return row_ptr.size() - 1;
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}
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}
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/*!
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* \brief get number of nonzero entries
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* \return number of nonzero entries
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*/
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inline size_t NumEntry( void ) const{
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return findex.size();
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}
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/*! \brief clear the storage */
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/*! \brief clear the storage */
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inline void Clear( void ){
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inline void Clear( void ){
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row_ptr.resize( 0 );
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row_ptr.resize( 0 );
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@ -164,6 +171,7 @@ namespace xgboost{
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}
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}
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}
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}
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};
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};
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};
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};
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};
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};
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#endif
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#endif
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@ -1,76 +0,0 @@
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#include"xgboost_data.h"
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#include<stdio.h>
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#include<vector>
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using namespace xgboost::booster;
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/*!
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* \file xgboost_gbmbase.h
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* \brief A reader to read the data for regression task from a specified file
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* The data should contain each data instance in each line.
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* The format of line data is as below:
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* label nonzero feature dimension[ feature index:feature value]+
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* \author Kailong Chen: chenkl198812@gmail.com
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*/
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class xgboost_regression_data_reader{
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public:
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xgboost_regression_data_reader(const char* file_path){
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Load(file_path);
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}
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void Load(const char* file_path){
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data_matrix.Clear();
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FILE* file = fopen(file_path,"r");
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if(file == NULL){
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printf("The file is missing at %s",file_path);
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return;
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}
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float label;
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int nonzero_dimension,index,value,num_row = 0;
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std::vector<bst_uint> findex;
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std::vector<bst_float> fvalue;
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while(fscanf(file,"%f %i",label,nonzero_dimension)){
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findex.clear();
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fvalue.clear();
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findex.resize(nonzero_dimension);
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fvalue.resize(nonzero_dimension);
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for(int i = 0; i < nonzero_dimension; i++){
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if(!fscanf(file," %i:%f",index,value)){
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printf("The feature dimension is not coincident \
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with the indicated one");
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return;
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}
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findex.push_back(index);
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fvalue.push_back(value);
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}
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data_matrix.AddRow(findex, fvalue);
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labels.push_back(label);
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num_row++;
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}
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printf("%i rows of data is loaded from %s",num_row,file_path);
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fclose(file);
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}
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float GetLabel(int index){
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return labels[index];
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}
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FMatrixS::Line GetLine(int index){
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return data_matrix[index];
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}
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int InsNum(){
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return labels.size();
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}
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FMatrixS::Image GetImage(){
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return FMatrixS::Image(data_matrix);
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}
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private:
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FMatrixS data_matrix;
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std::vector<float> labels;
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};
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132
regression/xgboost_regdata.h
Normal file
132
regression/xgboost_regdata.h
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@ -0,0 +1,132 @@
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#ifndef _XGBOOST_REGDATA_H_
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#define _XGBOOST_REGDATA_H_
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/*!
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* \file xgboost_regdata.h
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* \brief input data structure for regression and binary classification task.
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* Format:
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* The data should contain each data instance in each line.
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* The format of line data is as below:
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* label <nonzero feature dimension> [feature index:feature value]+
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* \author Kailong Chen: chenkl198812@gmail.com, Tianqi Chen: tianqi.tchen@gmail.com
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*/
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#include <cstdio>
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#include <vector>
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#include "../booster/xgboost_data.h"
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#include "../utils/xgboost_utils.h"
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#include "../utils/xgboost_stream.h"
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namespace xgboost{
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namespace regression{
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/*! \brief data matrix for regression content */
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struct DMatrix{
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public:
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/*! \brief maximum feature dimension */
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unsigned num_feature;
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/*! \brief feature data content */
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booster::FMatrixS data;
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/*! \brief label of each instance */
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std::vector<float> labels;
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public:
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/*! \brief default constructor */
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DMatrix( void ){}
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/*!
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* \brief load from text file
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* \param fname name of text data
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* \param silent whether print information or not
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*/
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inline void LoadText( const char* fname, bool silent = false ){
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data.Clear();
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FILE* file = utils::FopenCheck( fname, "r" );
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float label;
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int nonzero_dimension;
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std::vector<booster::bst_uint> findex;
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std::vector<booster::bst_float> fvalue;
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while( fscanf(file,"%f %d",&label,&nonzero_dimension) == 2 ){
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findex.clear(); fvalue.clear();
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for( int i = 0; i < nonzero_dimension; i++ ){
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unsigned index; float value;
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utils::Assert( fscanf(file, "%d:%f", &index, &value ) == 2,
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"The feature dimension is not coincident with the indicated one" );
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findex.push_back(index); fvalue.push_back(value);
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}
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data.AddRow( findex, fvalue );
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labels.push_back( label );
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}
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this->UpdateInfo();
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if( !silent ){
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printf("%ux%u matrix with %lu entries is loaded from %s\n",
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(unsigned)labels.size(), num_feature, (unsigned long)data.NumEntry(), fname );
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}
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fclose(file);
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}
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/*!
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* \brief load from binary file
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* \param fname name of binary data
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* \param silent whether print information or not
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* \return whether loading is success
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*/
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inline bool LoadBinary( const char* fname, bool silent = false ){
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FILE *fp = fopen64( fname, "rb" );
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if( fp == NULL ) return false;
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utils::FileStream fs( fp );
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data.LoadBinary( fs );
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labels.resize( data.NumRow() );
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utils::Assert( fs.Read( &labels[0], sizeof(float) * data.NumRow() ) != 0, "DMatrix LoadBinary" );
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fs.Close();
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this->UpdateInfo();
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if( !silent ){
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printf("%ux%u matrix with %lu entries is loaded from %s\n",
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(unsigned)labels.size(), num_feature, (unsigned long)data.NumEntry(), fname );
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}
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return true;
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}
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/*!
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* \brief save to binary file
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* \param fname name of binary data
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* \param silent whether print information or not
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*/
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inline void SaveBinary( const char* fname, bool silent = false ){
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utils::FileStream fs( utils::FopenCheck( fname, "wb" ) );
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data.SaveBinary( fs );
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fs.Write( &labels[0], sizeof(float) * data.NumRow() );
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fs.Close();
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if( !silent ){
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printf("%ux%u matrix with %lu entries is saved to %s\n",
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(unsigned)labels.size(), num_feature, (unsigned long)data.NumEntry(), fname );
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}
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}
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/*!
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* \brief cache load data given a file name, the function will first check if fname + '.xgbuffer' exists,
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* if binary buffer exists, it will reads from binary buffer, otherwise, it will load from text file,
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* and try to create a buffer file
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* \param fname name of binary data
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* \param silent whether print information or not
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* \return whether loading is success
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*/
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inline void CacheLoad( const char *fname, bool silent = false ){
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char bname[ 1024 ];
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sprintf( bname, "%s.buffer", fname );
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if( !this->LoadBinary( bname, silent ) ){
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this->LoadText( fname, silent );
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this->SaveBinary( fname, silent );
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}
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}
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private:
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/*! \brief update num_feature info */
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inline void UpdateInfo( void ){
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this->num_feature = 0;
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for( size_t i = 0; i < data.NumRow(); i ++ ){
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booster::FMatrixS::Line sp = data[i];
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for( unsigned j = 0; j < sp.len; j ++ ){
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if( num_feature <= sp.findex[j] ){
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num_feature = sp.findex[j] + 1;
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}
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}
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}
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}
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};
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};
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};
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#endif
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