Changeset 866 for trunk/yat/classifier

Timestamp:

Sep 12, 2007, 2:25:28 PM (16 years ago)

Author:

Markus Ringnér

Message:

refs #236. EnsembleBuilder::predict bug fixed for matrix-based classifiers. However this is not the case for Kernel-based classifiers!

File:

• trunk/yat/classifier/EnsembleBuilder.cc (modified) (4 diffs)

trunk/yat/classifier/EnsembleBuilder.cc

@@ -28 +28 @@
 #include "FeatureSelector.h"
 #include "KernelLookup.h"
+#include "MatrixLookup.h"
+#include "MatrixLookupWeighted.h"
 #include "Sampler.h"
 #include "SubsetGenerator.h"
@@ -82 +84 @@
 
 
-  void  EnsembleBuilder::predict
+  void EnsembleBuilder::predict
   (const DataLookup2D& data, 
    std::vector<std::vector<statistics::Averager> >& result)
@@ -92 +94 @@
     
     utility::matrix prediction;  
-    const KernelLookup* kernel = dynamic_cast<const KernelLookup*>(&data);
-    if (kernel) {
-      for(u_long k=0;k<subset_->size();k++) {
+    
+    const KernelLookup* kernel = dynamic_cast<const KernelLookup*>(&data);    
+    const MatrixLookupWeighted* mw = 
+      dynamic_cast<const MatrixLookupWeighted*>(&data);   
+    const MatrixLookup* m = dynamic_cast<const MatrixLookup*>(&data);
+
+    if(kernel) {
+      for(u_long k=0;k<subset_->size();k++) {       
         KernelLookup sub_kernel(*kernel,subset_->training_index(k),true);
         classifier(k).predict(sub_kernel,prediction);
-
-        for(size_t i=0; i<prediction.rows();i++) 
-          for(size_t j=0; j<prediction.columns();j++) 
-            result[i][j].add(prediction(i,j));
+      }
+    }
+    else if(mw) {
+      for(u_long k=0;k<subset_->size();k++) {
+        MatrixLookupWeighted sub_matrix(*mw,subset_->training_features(k),true);
+        classifier(k).predict(sub_matrix,prediction);
+      }
+    }
+    else if(m) {
+      for(u_long k=0;k<subset_->size();k++) {       
+        MatrixLookup sub_matrix(*m,subset_->training_features(k),true);
+        classifier(k).predict(sub_matrix,prediction);       
       }
     }
     else {
-      for(u_long k=0;k<subset_->size();k++) {
-        classifier(k).predict(data,prediction);
-        for(size_t i=0; i<prediction.rows();i++) 
-          for(size_t j=0; j<prediction.columns();j++) 
-            result[i][j].add(prediction(i,j));
-        
-      }
+      std::string str;
+      str = "Error in NCC::predict: DataLookup2D of unexpected class.";
+      throw std::runtime_error(str);
     }
+
+    for(size_t i=0; i<prediction.rows();i++) 
+      for(size_t j=0; j<prediction.columns();j++) 
+        result[i][j].add(prediction(i,j));    
   }
 
-
+  
   const std::vector<std::vector<statistics::Averager> >& 
   EnsembleBuilder::validate(void)
@@ -127 +142 @@
     for(u_long k=0;k<subset_->size();k++) {
       classifier(k).predict(subset_->validation_data(k),prediction);
-
+      
+      // map results to indices of samples in training + validation data set
       for(size_t i=0; i<prediction.rows();i++) 
         for(size_t j=0; j<prediction.columns();j++) {