Changeset 525 for trunk/lib/classifier/NCC.cc

Timestamp:

Feb 24, 2006, 5:29:22 PM (17 years ago)

Author:

Markus Ringnér

Message:

Added structure to Supervised classifier and NCC to support ranking inputs with a statistics::Score and using only top-scoring inputs in classification.

File:

• trunk/lib/classifier/NCC.cc (modified) (5 diffs)

trunk/lib/classifier/NCC.cc

@@ -5 +5 @@
 #include <c++_tools/classifier/DataLookup1D.h>
 #include <c++_tools/classifier/DataLookup2D.h>
+#include <c++_tools/classifier/InputRanker.h>
 #include <c++_tools/classifier/Target.h>
 #include <c++_tools/gslapi/vector.h>
@@ -24 +25 @@
   }
 
+  NCC::NCC(const DataLookup2D& data, const Target& target, 
+           const statistics::Distance& distance, 
+           statistics::Score& score, size_t nof_inputs) 
+    : SupervisedClassifier(target, &score, nof_inputs), 
+      distance_(distance), matrix_(data)
+  {
+  }
+
+  NCC::~NCC()   
+  {
+    if(ranker_)
+      delete ranker_;
+  }
+
+
   SupervisedClassifier* 
   NCC::make_classifier(const DataLookup2D& data, 
                        const Target& target) const 
   {     
-    NCC* sc= new NCC(data,target,this->distance_);
-    return sc;
+    NCC* ncc= new NCC(data,target,this->distance_);
+    ncc->score_=this->score_;
+    ncc->nof_inputs_=this->nof_inputs_;
+    return ncc;
   }
 
@@ -35 +53 @@
   bool NCC::train()
   {
+    if(ranker_)
+      delete ranker_;
+    if(score_)
+      ranker_=new InputRanker(matrix_, target_, *score_);
+    // Markus : ranker_ should be taken into account if used!!!
+
     // Calculate the centroids for each class
     centroids_=gslapi::matrix(matrix_.rows(),target_.nof_classes());
@@ -54 +78 @@
                     gslapi::vector& prediction) const
   {
+    // Markus : ranker_ should be taken into account if used!!!
+
     prediction=gslapi::vector(centroids_.columns());    
     gslapi::vector w(input.size(),0);
@@ -68 +94 @@
                     gslapi::matrix& prediction) const
   {
+    // Markus : ranker_ should be taken into account if used!!!
+    
     prediction=gslapi::matrix(centroids_.columns(), input.columns());   
     for(size_t j=0; j<input.columns();j++) {