[Jboost-cvs] jboost/src/jboost/booster BrownBoost.java,1.3,1.4

[Aaron A. <aa...@us...>]

Update of /cvsroot/jboost/jboost/src/jboost/booster
In directory sc8-pr-cvs6.sourceforge.net:/tmp/cvs-serv24459/src/jboost/booster

Modified Files:
	BrownBoost.java 
Log Message:
Bug fix for weight and potential updates when hypothesis abstains

Index: BrownBoost.java
===================================================================
RCS file: /cvsroot/jboost/jboost/src/jboost/booster/BrownBoost.java,v
retrieving revision 1.3
retrieving revision 1.4
diff -C2 -d -r1.3 -r1.4
*** BrownBoost.java	4 Jun 2007 07:24:38 -0000	1.3
--- BrownBoost.java	14 Jun 2007 16:45:52 -0000	1.4
***************
*** 41,44 ****
--- 41,54 ----
      protected double[] m_hypPredictions;
    
+     /** 
+      * Records the potentials.  Similar to m_margins and m_weights.
+      */
+     protected double[] m_potentials;
+   
+     /** 
+      * Records the potentials.  Similar to m_margins and m_weights.
+      */
+     protected double m_totalPotential;
+   
      /**
       * Default constructor just calls AdaBoost to 
***************
*** 49,52 ****
--- 59,71 ----
      }
  
+ 
+     public void finalizeData() {
+ 	super.finalizeData();
+         m_potentials = new double[m_numExamples];
+ 	for (int i=0; i<m_numExamples; i++) {
+ 	    m_potentials[i] = calculatePotential(0,m_c);
+ 	}
+     }
+ 
      public void setRuntime(double runtime){
  	m_c = runtime;
***************
*** 316,320 ****
          int count_t_over_s = 0;
          double lastE = 0;
!         double STEP_EPS = 0.00001;
  	double CORR_EPS = 0.001;
          boolean first_iter = true;
--- 335,339 ----
          int count_t_over_s = 0;
          double lastE = 0;
!         double STEP_EPS = 0.0001;
  	double CORR_EPS = 0.001;
          boolean first_iter = true;
***************
*** 365,375 ****
                  if(sign(vars.B) != sign(alpha_step)) alpha_step /= -2;
  		if(Math.abs(vars.B) < CORR_EPS) break;
- 		/*
- 		  if (alpha > 5) {
- 		  alpha = 0.1; 
- 		  vars = calc_constraints (alpha, t);
- 		  break;
- 		  }
- 		*/
              }
  
--- 384,387 ----
***************
*** 388,399 ****
          double bs_t = t;
  
- 
-     /*
- 	System.out.println("\nBinary Search gives alpha=" + bs_alpha
- 			   + ", t=" + bs_t + ", s=" + m_s 
- 			   + ", pot_diff=" + vars.E
- 			   + ", pot=" + vars.Potential);
-     */
- 
  	alpha = bs_alpha;
  	t = bs_t;
--- 400,403 ----
***************
*** 415,421 ****
  	return alpha;
      }
-   
- 
  
    
      /**
--- 419,430 ----
  	return alpha;
      }
  
+     public String surfingData() {
+ 	String ret = new String("");
+ 	for (int i=0; i<m_margins.length; i++){
+ 	    ret += String.format("%.4f\t%.4f\t%.4f\n", m_margins[i], m_weights[i], m_potentials[i]);
+ 	}
+ 	return ret;
+     }
    
      /**
***************
*** 432,445 ****
  	    return;
  	}
- 
- 	// save old m_weights
- 	for (int i= 0; i < m_weights.length; i++){
- 	    m_oldWeights[i]= m_weights[i];
- 	}
- 
- 	// save old m_margins
- 	for (int i= 0; i < m_margins.length; i++){
- 	    m_oldMargins[i] = m_margins[i];
- 	}
      
  	for (int i= 0; i < exampleIndex.length; i++) {
--- 441,444 ----
***************
*** 449,460 ****
  	    for (int j= 0; j < indexes.length; j++) {
  		int example   = indexes[j];
  		m_margins[example] += value[m_labels[example]];
  	    }
  	}
  
          for (int i=0; i < m_hypPredictions.length; i++) {
!             m_totalWeight -= m_weights[i];
              m_weights[i] = calculateWeight(m_margins[i]);
              m_totalWeight += m_weights[i];
          }
      }
--- 448,467 ----
  	    for (int j= 0; j < indexes.length; j++) {
  		int example   = indexes[j];
+ 		m_oldMargins[example] = m_margins[example];
  		m_margins[example] += value[m_labels[example]];
  	    }
  	}
  
+ 	
+ 	m_totalWeight = 0;
+ 	m_totalPotential = 0;
          for (int i=0; i < m_hypPredictions.length; i++) {
! 	    m_oldWeights[i]= m_weights[i];
! 
              m_weights[i] = calculateWeight(m_margins[i]);
              m_totalWeight += m_weights[i];
+ 
+             m_potentials[i] = calculatePotential(m_margins[i]);
+             m_totalPotential += m_potentials[i];
          }
      }
***************
*** 605,623 ****
  	gamma /= total_weight;
  	potential /= m_margins.length;
- 	/*
- 	System.out.println("---------------------------------------");
- 	System.out.println("---------------------------------------");
- 	System.out.print("gamma (weighted correlation):" + gamma);
- 	System.out.print(", potential (unweighted):" + potential);
- 	System.out.print(", hyp error (unweighted):" + hyp_err + "\n");
- 	System.out.println("");
- 	*/
  
  	/*
! 	if (total_err < m_initialPotential) {
! 	    System.err.println("WARNING: the 'weak' hypothesis was too good!");
! 	    System.err.println("You were aiming for an error rate of: " + m_initialPotential);
! 	    System.err.println("With this hypothesis, you were able to achieve an error rate of: " + total_err);
! 	}
  	*/
  
--- 612,621 ----
  	gamma /= total_weight;
  	potential /= m_margins.length;
  
  	/*
! 	System.out.println("\tTotal number of examples: " + m_margins.length);
! 	System.out.println("\tNumber of predictions made: " + num_predictions);
! 	String out = "\tgamma (weighted correlation):" + gamma + ", potential (unweighted):" + potential + ", hyp error (unweighted):" + hyp_err;
! 	System.out.println(out);
  	*/