add auc evaluation metric

regression/xgboost_reg.h

@@ -172,7 +172,7 @@ namespace xgboost{
                 preds.resize(data.Size());
 
                 const unsigned ndata = static_cast<unsigned>(data.Size());
-#pragma omp parallel for schedule( static )
+                #pragma omp parallel for schedule( static )
                 for (unsigned j = 0; j < ndata; ++j){
                     preds[j] = mparam.PredTransform
                         (mparam.base_score + base_gbm.Predict(data.data, j, -1));
@@ -233,7 +233,7 @@ namespace xgboost{
                 preds.resize(data.Size());
 
                 const unsigned ndata = static_cast<unsigned>(data.Size());
-#pragma omp parallel for schedule( static )
+                #pragma omp parallel for schedule( static )
                 for (unsigned j = 0; j < ndata; ++j){
                     preds[j] = mparam.PredTransform
                         (mparam.base_score + base_gbm.Predict(data.data, j, buffer_offset + j));
@@ -248,7 +248,7 @@ namespace xgboost{
                 grad.resize(preds.size()); hess.resize(preds.size());
 
                 const unsigned ndata = static_cast<unsigned>(preds.size());
-#pragma omp parallel for schedule( static )
+                #pragma omp parallel for schedule( static )
                 for (unsigned j = 0; j < ndata; ++j){
                     grad[j] = mparam.FirstOrderGradient(preds[j], labels[j]);
                     hess[j] = mparam.SecondOrderGradient(preds[j], labels[j]);

regression/xgboost_reg_eval.h

@@ -11,6 +11,7 @@
 #include <algorithm>
 #include "../utils/xgboost_utils.h"
 #include "../utils/xgboost_omp.h"
+#include "../utils/xgboost_random.h"
 
 namespace xgboost{
     namespace regression{
@@ -33,7 +34,7 @@ namespace xgboost{
                                const std::vector<float> &labels) const{
                 const unsigned ndata = static_cast<unsigned>(preds.size());
                 float sum = 0.0;
-#pragma omp parallel for reduction(+:sum) schedule( static )
+                #pragma omp parallel for reduction(+:sum) schedule( static )
                 for (unsigned i = 0; i < ndata; ++i){
                     float diff = preds[i] - labels[i];
                     sum += diff * diff;
@@ -51,7 +52,7 @@ namespace xgboost{
                                const std::vector<float> &labels) const{
                 const unsigned ndata = static_cast<unsigned>(preds.size());
                 unsigned nerr = 0;
-#pragma omp parallel for reduction(+:nerr) schedule( static )
+                #pragma omp parallel for reduction(+:nerr) schedule( static )
                 for (unsigned i = 0; i < ndata; ++i){
                     if (preds[i] > 0.5f){
                         if (labels[i] < 0.5f) nerr += 1;
@@ -67,6 +68,38 @@ namespace xgboost{
             }
         };
 
+        /*! \brief Area under curve */
+        struct EvalAuc : public IEvaluator{         
+            inline static bool CmpFirst( const std::pair<float,float> &a, const std::pair<float,float> &b ){
+                return a.first > b.first;
+            }
+            virtual float Eval( const std::vector<float> &preds, 
+                                const std::vector<float> &labels ) const{
+                const unsigned ndata = static_cast<unsigned>( preds.size() );
+                std::vector< std::pair<float, float> > rec;
+                for( unsigned i = 0; i < ndata; ++ i ){
+                    rec.push_back( std::make_pair( preds[i], labels[i]) );
+                }
+                random::Shuffle( rec );
+                std::sort( rec.begin(), rec.end(), CmpFirst );
+
+                long npos = 0, nhit = 0;
+                for( unsigned i = 0; i < ndata; ++ i ){
+                    if( rec[i].second > 0.5f ) {
+                        ++ npos; 
+                    }else{
+                        // this is the number of correct pairs
+                        nhit += npos;
+                    }
+                } 
+                long nneg = ndata - npos;
+                utils::Assert( nneg > 0, "the dataset only contains pos samples" );
+                return static_cast<float>(nhit) / nneg / npos;
+            }
+            virtual const char *Name( void ) const{
+                return "auc";
+            }
+        };
 
         /*! \brief Error */
         struct EvalLogLoss : public IEvaluator{
@@ -74,7 +107,7 @@ namespace xgboost{
                                const std::vector<float> &labels) const{
                 const unsigned ndata = static_cast<unsigned>(preds.size());
                 unsigned nerr = 0;
-#pragma omp parallel for reduction(+:nerr) schedule( static )
+                #pragma omp parallel for reduction(+:nerr) schedule( static )
                 for (unsigned i = 0; i < ndata; ++i){
                     const float y = labels[i];
                     const float py = preds[i];
@@ -96,6 +129,7 @@ namespace xgboost{
                 if (!strcmp(name, "rmse")) evals_.push_back(&rmse_);
                 if (!strcmp(name, "error")) evals_.push_back(&error_);
                 if (!strcmp(name, "logloss")) evals_.push_back(&logloss_);
+                if (!strcmp( name, "auc"))   evals_.push_back( &auc_ );
             }
             inline void Init(void){
                 std::sort(evals_.begin(), evals_.end());
@@ -112,6 +146,7 @@ namespace xgboost{
         private:
             EvalRMSE  rmse_;
             EvalError error_;
+            EvalAuc   auc_;
             EvalLogLoss logloss_;
             std::vector<const IEvaluator*> evals_;
         };