Merge branch 'master' into cluster

Conflicts:

	main.cc
	parse_example.cc
	vw.cc

1 files changed, 24 insertions, 23 deletions

diff --git a/main.cc b/main.cc
index bb39c978..c61761e8 100644
--- a/main.cc
+++ b/main.cc
@@ -7,28 +7,29 @@ embodied in the content of this file are licensed under the BSD
 #include "vw.h"
 #include "gd.h"
 
+int main(int argc, char *argv[]) {
+	gd_vars *vars = vw(argc, argv);
 
-int main(int argc, char *argv[]) 
-{
-  gd_vars *vars = vw(argc, argv);
-  
-  float best_constant = vars->weighted_labels / vars->weighted_examples;
-  float constant_loss = (best_constant*(1.0 - best_constant)*(1.0 - best_constant)
-			 + (1.0 - best_constant)*best_constant*best_constant);
-  
-  if (!vars->quiet)
-    {
-      cerr.precision(4);
-      cerr << endl << "finished run";
-      cerr << endl << "number of examples = " << vars->example_number;
-      cerr << endl << "weighted example sum = " << vars->weighted_examples;
-      cerr << endl << "weighted label sum = " << vars->weighted_labels;
-      cerr << endl << "average loss = " << vars->sum_loss / vars->weighted_examples;
-      cerr << endl << "best constant's loss = " << constant_loss;
-      cerr << endl << "total feature number = " << vars->total_features;
-      cerr << endl;
-    }
-  delete vars;
-  
-  return 0;
+	float best_constant = vars->weighted_labels / vars->weighted_examples;
+	float constant_loss = (best_constant*(1.0 - best_constant)*(1.0 - best_constant)
+			+ (1.0 - best_constant)*best_constant*best_constant);
+
+	if (!vars->quiet)
+	{
+		cerr.precision(4);
+		cerr << endl << "finished run";
+		cerr << endl << "number of examples = " << vars->example_number;
+		cerr << endl << "weighted example sum = " << vars->weighted_examples;
+		cerr << endl << "weighted label sum = " << vars->weighted_labels;
+		cerr << endl << "average loss = " << vars->sum_loss / vars->weighted_examples;
+		cerr << endl << "best constant = " << best_constant;
+		if (vars->min_prediction == 0. && vars->max_prediction == 1. && best_constant < 1. && best_constant > 0.)
+		  cerr << endl << "best constant's loss = " << constant_loss;
+		cerr << endl << "total feature number = " << vars->total_features;
+		cerr << endl;
+	}
+
+	free(vars);
+
+	return 0;
 }