Changeset 36 for trunk/src/SVM.cc

Timestamp:

Feb 12, 2004, 11:29:21 AM (19 years ago)

Author:

Peter

Message:

stop criteria for the traing modified

File:

• trunk/src/SVM.cc (modified) (2 diffs)

trunk/src/SVM.cc

@@ -34 +34 @@
   double u;
   double v;
+  thep_gsl_api::vector dalpha;  
   
   // Stop criteria  
-  ofstream myout("alpha.tst");
-  double tmp;
-  thep_gsl_api::vector dalpha;  
-  thep_gsl_api::vector one(E.size(),true,true);
-  one.set_all(1);
-  while (count<10000)
+  bool stop_condition = false;
+  while(count<100000 && !stop_condition)
     {
      count++;  
      dalpha = alpha_.mul_elements(target_);
-     E=kernel_*dalpha-target_; //should be done in another way!!
-     tmp=dalpha*(kernel_*dalpha)/2;
-     tmp=tmp-alpha_*one;
-     myout << tmp << '\n';
+     E = kernel_*dalpha-target_; //should be done in another way!!
+       
      // Choosing a pair of variables to modify (Should be done more clever)
      u_long index1 = rnd->get_uniform_int(kernel_.cols());
@@ -94 +89 @@
      alpha_[index1]+=target_[index1]*target_[index2]*(alpha_[index2]-alpha_new);
      alpha_[index2]=alpha_new;
-     
-     
-     
-     
-    
-
+     stop_condition = stop( target_, kernel_, alpha_);
     }
   
-  myout.close();
-  
-  //thep_gsl_api::vector output = kernel_*dalpha;
-  //for (int i=0; i<64; i++){ 
-  //cout << output.get(i) << '\t';
-  //cout << alpha_.get(i) << endl;
-  //}
-
   trained_= true;
 }
 
+bool SVM::stop( const thep_gsl_api::vector& target_,
+    const thep_gsl_api::matrix& kernel_,
+    const thep_gsl_api::vector& alpha_)
+{
+  double min_output_positive = 10000;
+  double max_output_negative = -10000;
+  double epsilon = 0.001; // used twice, should perhaps be two different values
+  thep_gsl_api::vector output_unbiased = kernel_ * alpha_.mul_elements(target_);
+  for (u_int i=0; i<target_.size(); i++){
+   if (target_[i]==1){
+     if (output_unbiased[i] < min_output_positive)
+       min_output_positive = output_unbiased[i];
+   }
+   else if( output_unbiased[i] > max_output_negative )
+     max_output_negative = output_unbiased[i];
+   
+  }
+  
+  if (min_output_positive - max_output_negative < 2-epsilon){
+   return false;
+  }
+  else{
+   double primal = alpha_.mul_elements(target_)
+     *  ( alpha_.mul_elements(target_) );
+   double gap = 2 * primal - alpha_.sum();
+   if (gap/(primal+1)<epsilon)
+     return true;
+   else
+     return false;
+  }
+
+
+}
+
+
+
 #endif