[Jboost-cvs] jboost/src/jboost/booster AdaBoost.java,1.6,1.6.2.1

SourceForge Headquarters 225 Broadway Suite 1600 San Diego, CA 92101 +1 (858) 422-6466

Update of /cvsroot/jboost/jboost/src/jboost/booster
In directory sc8-pr-cvs17.sourceforge.net:/tmp/cvs-serv23957/src/jboost/booster

Modified Files:
      Tag: jboost_unstable
	AdaBoost.java 
Log Message:
clean-up

Index: AdaBoost.java
===================================================================
RCS file: /cvsroot/jboost/jboost/src/jboost/booster/AdaBoost.java,v
retrieving revision 1.6
retrieving revision 1.6.2.1
diff -C2 -d -r1.6 -r1.6.2.1
*** AdaBoost.java	25 Mar 2008 01:00:27 -0000	1.6
--- AdaBoost.java	7 Apr 2008 17:21:47 -0000	1.6.2.1
***************
*** 28,32 ****
    protected double[] m_margins;
    /** permanent storage for old m_margins */
!   protected double[] m_oldMargins;
    /** permanent storage for example m_weights */
    protected double[] m_weights;
--- 28,32 ----
    protected double[] m_margins;
    /** permanent storage for old m_margins */
!   protected double[] m_oldMargins; // XXX DJH: this is never used in AdaBoost (e.g. not cleared in clear())
    /** permanent storage for example m_weights */
    protected double[] m_weights;
***************
*** 73,77 ****
  
    /** temporary location for storing the examples as they are read in */
!   protected List m_tmpList;
  
  
--- 73,77 ----
  
    /** temporary location for storing the examples as they are read in */
!   protected List<TmpData> m_tmpList;
  
  
***************
*** 90,94 ****
     */
    AdaBoost(double smooth) {
!     m_tmpList= new ArrayList();
      m_numExamples= 0;
      m_smooth= smooth;
--- 90,94 ----
     */
    AdaBoost(double smooth) {
!     m_tmpList= new ArrayList<TmpData>();
      m_numExamples= 0;
      m_smooth= smooth;
***************
*** 104,113 ****
    }
  
!  /**
!   * Add an example to the data set of this booster
!   * @param index
!   * @param label
!   * @param weight
!   */
    public void addExample(int index, Label label, double weight) {
      int l= label.getSingleValue();
--- 104,113 ----
    }
  
!   /**
!    * Add an example to the data set of this booster
!    * @param index
!    * @param label
!    * @param weight
!    */
    public void addExample(int index, Label label, double weight) {
      int l= label.getSingleValue();
***************
*** 119,128 ****
          if (l==POSITIVE_LABEL) m_numPosExamples++;
        } else {
!         failed= "AdaBoost.addExample received index " + index + ", when it expected index " +
!                   m_numExamples;
        }
      } else {
!       failed= "Adaboost.addExample expected a label which is either 0 or 1. It received " +
!                l;
      }
  
--- 119,128 ----
          if (l==POSITIVE_LABEL) m_numPosExamples++;
        } else {
!         // XXX DJH: determine class name at runtime
!         failed= getClass().getName() + ".addExample received index " + index + ", when it expected index " + m_numExamples;
        }
      } else {
!       // XXX DJH: determine class name at runtime
!       failed= getClass().getName() + ".addExample expected a label which is either 0 or 1. It received " + l;
      }
  
***************
*** 181,185 ****
          m_negExamples[m_negIndex++] = index;
        else {
!         System.err.println("Label of example is unknown to adaboost");
          System.exit(2);
        }
--- 181,186 ----
          m_negExamples[m_negIndex++] = index;
        else {
!         // XXX DJH: determine class name at runtime
!         System.err.println("Label of example is unknown to " + this.getClass().getName());
          System.exit(2);
        }
***************
*** 248,278 ****
  
  
!     /**
!      * Returns a string with all the weights, margins, etc
!      */
!     public String getExampleData() {
!         StringBuffer ret = new StringBuffer("");
!         ret.append(getParamString());
!         for (int i=0; i<m_margins.length; i++){
!             ret.append(String.format("[%d];[%.4f];[%.4f];[%.4f];\n",
! 				     m_labels[i], m_margins[i], m_weights[i],
! 				     m_potentials[i]));
!         }
!         return ret.toString();
      }
  
!     public String getParamString() {
!         String ret = String.format("None (AdaBoost)");
!         return ret;
!     }
  
  
    /** output AdaBoost contents as a human-readable string */
    public String toString() {
      String s=
!       "Adaboost. No of examples = "
!         + m_numExamples
!         + ", m_epsilon = "
!         + m_epsilon;
      s += "\nindex\tmargin\tweight\told weight\tlabel\n";
      NumberFormat f= new DecimalFormat("0.00");
--- 249,282 ----
  
  
!   /**
!    * Returns a string with all the weights, margins, etc
!    */
!   public String getExampleData() {
!     StringBuffer ret = new StringBuffer("");
!     ret.append(getParamString());
!     for (int i=0; i<m_margins.length; i++){
!       ret.append(String.format("[%d];[%.4f];[%.4f];[%.4f];\n",
!           m_labels[i], m_margins[i], m_weights[i],
!           m_potentials[i]));
      }
+     return ret.toString();
+   }
  
!   public String getParamString() {
!     // XXX DJH: determine class name at runtime
!     String ret = String.format("None (" + getClass().getName() + ")");
!     return ret;
!   }
  
  
    /** output AdaBoost contents as a human-readable string */
    public String toString() {
+     // XXX DJH: determine class name at runtime
      String s=
!       getClass().getName() +
!       ". No of examples = "
!       + m_numExamples
!       + ", m_epsilon = "
!       + m_epsilon;
      s += "\nindex\tmargin\tweight\told weight\tlabel\n";
      NumberFormat f= new DecimalFormat("0.00");
***************
*** 289,293 ****
          + f.format(m_sampleWeights[i]) + "\t\t"
          + m_labels[i]
!         + "\n";
      }
      return s;
--- 293,297 ----
          + f.format(m_sampleWeights[i]) + "\t\t"
          + m_labels[i]
!                    + "\n";
      }
      return s;
***************
*** 353,357 ****
     * @return +1 if label matches hyp, -1 if label doesn't match hyp, 0 if no hyp
     */
!   public double getStep(short simple_label, double hyp_pred) {
      double step = getLabel(simple_label)*hyp_pred;
      double EPS = 0.000001;
--- 357,362 ----
     * @return +1 if label matches hyp, -1 if label doesn't match hyp, 0 if no hyp
     */
!   // XXX DJH: changed from 'public' to 'protected'
!   protected double getStep(short simple_label, double hyp_pred) {
      double step = getLabel(simple_label)*hyp_pred;
      double EPS = 0.000001;
***************
*** 360,364 ****
    }
  
!   public double getLabel(short simple_label) {
      return sign(-simple_label+0.5);
    }
--- 365,370 ----
    }
  
!   // XXX DJH: changed from 'public' to 'protected'
!   protected double getLabel(short simple_label) {
      return sign(-simple_label+0.5);
    }
***************
*** 369,373 ****
      double total_weight = 0.0;
  
!     // Keep track of which hypotheses had hypotheses associated with them.
      boolean[] examplesWithHyp = new boolean[m_margins.length];
      m_hypPredictions = new double[m_margins.length];
--- 375,379 ----
      double total_weight = 0.0;
  
!     // Keep track of which examples had hypotheses associated with them.
      boolean[] examplesWithHyp = new boolean[m_margins.length];
      m_hypPredictions = new double[m_margins.length];
***************
*** 378,384 ****
          int example = index[j];
          if (this instanceof BrownBoost)
!             m_hypPredictions[example] = ((BrownBag)b).calcPrediction(1.0,1.0).getClassScores()[0];
!           else
!             m_hypPredictions[example] = b.calcPrediction().getClassScores()[0];
        }
      }
--- 384,390 ----
          int example = index[j];
          if (this instanceof BrownBoost)
!           m_hypPredictions[example] = ((BrownBag)b).calcPrediction(1.0,1.0).getClassScores()[0];
!         else
!           m_hypPredictions[example] = b.calcPrediction().getClassScores()[0];
        }
      }
***************
*** 386,390 ****
  
      int numExamplesWithHyps = 0;
-     double weight;
      // Get all examples that have a hypothesis associated with them
      for (int i= 0; i < exampleIndex.length; i++) {
--- 392,395 ----
***************
*** 442,446 ****
        }
      }*/
-     double gamma = getHypErr(bags, exampleIndex);
      return getPredictions(bags);
    }
--- 447,450 ----
***************
*** 452,456 ****
     */
    public double calculateWeight(double margin) {
!   	return Math.exp(-1 * margin);
    }
  
--- 456,460 ----
     */
    public double calculateWeight(double margin) {
!     return Math.exp(-1 * margin);
    }
  
***************
*** 579,583 ****
        double EPS = 0.0000001;
        if (m_w[0] < EPS && m_w[1] < EPS) {
!     	  return true;
        }
        return false;
--- 583,587 ----
        double EPS = 0.0000001;
        if (m_w[0] < EPS && m_w[1] < EPS) {
!         return true;
        }
        return false;
***************
*** 665,672 ****
  
        BinaryPrediction p = new BinaryPrediction(
!         m_w[1] == m_w[0]
!         ? 0.0
!       : // handle case that w0=w1=0
!       0.5 * Math.log((m_w[1] + smoothFactor) / (m_w[0] + smoothFactor)));
        return p;
      }
--- 669,676 ----
  
        BinaryPrediction p = new BinaryPrediction(
!           m_w[1] == m_w[0]
!                         ? 0.0
!                             : // handle case that w0=w1=0
!                               0.5 * Math.log((m_w[1] + smoothFactor) / (m_w[0] + smoothFactor)));
        return p;
      }