Changeset 1076

Timestamp:

Feb 12, 2008, 2:51:11 PM (16 years ago)

Author:

Markus Ringnér

Message:

NCC done for ticket:259

Location:

trunk

Files:

• test/ncc_test.cc (modified) (1 diff)
• yat/classifier/NCC.h (modified) (2 diffs)

trunk/test/ncc_test.cc

@@ -134 +134 @@
   }
 
-  
+  //////////////////////////////////////////////////////////////////////////
+  // A test of predictions using weighted training resulting in NaN's
+  // in centroids and unweighted test data
+  //////////////////////////////////////////////////////////////////////////
+  *error << "test of predictions using nan centroids and unweighted test data\n";
+  utility::matrix weights2(3,4,1.0);
+  weights2(1,0)=weights2(1,1)=0.0;
+  classifier::MatrixLookupWeighted mlw2(data1,weights2);
+  classifier::NCC<statistics::EuclideanDistance> ncc2(mlw2,target1);
+  ncc2.train();
+  ncc2.predict(ml1,prediction1);  
+  result1(0,0)=result1(0,1)=result1(1,2)=result1(1,3)=sqrt(3.0);
+  result1(1,0)=result1(1,1)=sqrt(11.0);
+  result1(0,2)=result1(0,3)=sqrt(15.0);
+  slack = deviation(prediction1,result1);
+  if (slack > slack_bound || std::isnan(slack)){
+    *error << "Difference to expected prediction too large\n";
+    *error << "slack: " << slack << std::endl;
+    *error << "expected less than " << slack_bound << std::endl;
+    ok = false;
+  }
 
   //////////////////////////////////////////////////////////////////////////

trunk/yat/classifier/NCC.h

@@ -198 +198 @@
         }
         for(size_t c=0;c<target_.nof_classes();c++) {
-          (*centroids_)(i,c) = class_averager[c].mean();
-          if(class_averager[c].sum_w()==0)
+          if(class_averager[c].sum_w()==0) {
             centroids_nan_=true;
+            (*centroids_)(i,c) = std::numeric_limits<double>::quiet_NaN();
+          }
+          else {
+            (*centroids_)(i,c) = class_averager[c].mean();
+          }
         }
       }
@@ -235 +239 @@
     if (const MatrixLookup* test_unweighted =
         dynamic_cast<const MatrixLookup*>(&test)) {
-      // If weighted training data resulting in NaN in centroids: weighted calculations
+      // If weighted training data has resulted in NaN in centroids: weighted calculations
       if(centroids_nan_) { 
-        //        predict_weighted(MatrixLookupWeighted(*test_unweighted),prediction);
-        std::string str = 
-        "Error in NCC<Distance>::predict: weighted training unweighted test not implemented yet";
-      throw std::runtime_error(str);
+        predict_weighted(MatrixLookupWeighted(*test_unweighted),prediction);
       }
       // If unweighted training data: unweighted calculations