Changeset 898 for trunk/yat/classifier

Timestamp:

Sep 26, 2007, 3:44:19 PM (15 years ago)

Author:

Markus Ringnér

Message:

A first suggestion for how to adress #250. Also removed contamination of namespace std (see #251).

Location:

trunk/yat/classifier

Files:

• NCC.cc (modified) (5 diffs)
• NCC.h (modified) (4 diffs)

trunk/yat/classifier/NCC.cc

@@ -27 +27 @@
 #include "DataLookup1D.h"
 #include "DataLookup2D.h"
+#include "DataLookupWeighted1D.h"
 #include "MatrixLookup.h"
 #include "MatrixLookupWeighted.h"
 #include "Target.h"
+#include "yat/statistics/vector_distance.h"
+#include "yat/statistics/euclidean_vector_distance.h"
+#include "yat/utility/Iterator.h"
+#include "yat/utility/IteratorWeighted.h"
 #include "yat/utility/matrix.h"
 #include "yat/utility/vector.h"
-#include "yat/statistics/Distance.h"
 #include "yat/utility/stl_utility.h"
 
@@ -45 +49 @@
 
   NCC::NCC(const MatrixLookup& data, const Target& target, 
-           const statistics::Distance& distance) 
+           const statistics::vector_distance_lookup_weighted_ptr distance) 
     : SupervisedClassifier(target), distance_(distance), data_(data)
   {
@@ -51 +55 @@
 
   NCC::NCC(const MatrixLookupWeighted& data, const Target& target, 
-           const statistics::Distance& distance) 
+           const statistics::vector_distance_lookup_weighted_ptr distance) 
     : SupervisedClassifier(target), distance_(distance), data_(data)
   {
@@ -65 +69 @@
     return centroids_;
   }
+  
 
-    const DataLookup2D& NCC::data(void) const
-    {
+  const DataLookup2D& NCC::data(void) const
+  {
     return data_;
-    }
-
+  }
+  
   SupervisedClassifier* 
   NCC::make_classifier(const DataLookup2D& data, const Target& target) const 
@@ -109 +114 @@
   }
 
-
-  void NCC::predict(const utility::vector& input, const utility::vector& weights,
-                    utility::vector& prediction) const
-  {
-    prediction.clone(utility::vector(centroids_.columns()));
-    
-    // take care of nan's in centroids
-    for(size_t j=0; j<centroids_.columns(); j++) {
-      const utility::vector centroid(utility::vector(centroids_,j,false));
-      utility::vector wc(centroid.size(),0);
-      for(size_t i=0; i<centroid.size(); i++)  { 
-        if(!std::isnan(centroid(i)))
-          wc(i)=1.0;
-      }
-      prediction(j)=distance_(input,centroid,weights,wc);   
-    }
-  }
-
-
   void NCC::predict(const DataLookup2D& input,                    
                     utility::matrix& prediction) const
   {   
-    prediction.clone(utility::matrix(centroids_.columns(), input.columns()));
-    // weighted case
-    const MatrixLookupWeighted* data =
-      dynamic_cast<const MatrixLookupWeighted*>(&input);  
-    if (data) {
-      for(size_t j=0; j<input.columns();j++) {     
-        utility::vector in(input.rows(),0);
-        for(size_t i=0; i<in.size();i++) 
-          in(i)=data->data(i,j);
-        utility::vector weights(in.size(),0);
-        for(size_t i=0; i<in.size();i++) 
-          weights(i)=data->weight(i,j);
-        utility::vector out;
-        predict(in,weights,out);
-        prediction.column(j,out);
+    prediction.clone(utility::matrix(centroids_.columns(), input.columns()));   
+
+    // Weighted case
+    const MatrixLookupWeighted* testdata =
+      dynamic_cast<const MatrixLookupWeighted*>(&input);      
+    if (testdata) {
+      utility::matrix centroid_weights;
+      utility::nan(centroids_,centroid_weights);
+      MatrixLookupWeighted weighted_centroids(centroids_,centroid_weights);
+      for(size_t j=0; j<input.columns();j++) {        
+        DataLookupWeighted1D in(*testdata,j,false);
+        for(size_t k=0; k<centroids_.columns();k++) {
+          DataLookupWeighted1D centroid(weighted_centroids,k,false);
+          prediction(k,j)=(*distance_)(in.begin(),in.end(),centroid.begin());
+        }
       }
-      return;
     }
-    // non-weighted case
-    const MatrixLookup* x = dynamic_cast<const MatrixLookup*>(&input);
-    if (!x){
+    else {
       std::string str;
       str = "Error in NCC::predict: DataLookup2D of unexpected class.";
       throw std::runtime_error(str);
     }
-    for(size_t j=0; j<input.columns();j++) {     
-      utility::vector in(input.rows(),0);
-      for(size_t i=0; i<in.size();i++) 
-        in(i)=(*data)(i,j);
-      utility::vector weights(in.size(),1.0);
-      utility::vector out;
-      predict(in,weights,out);
-      prediction.column(j,out);
-    }
   }
-
-  
-  // additional operators
-
-//  std::ostream& operator<< (std::ostream& s, const NCC& ncc) {
-//    std::copy(ncc.classes().begin(), ncc.classes().end(), 
-//              std::ostream_iterator<std::map<double, u_int>::value_type>
-//              (s, "\n"));
-//    s << "\n" << ncc.centroids() << "\n";
-//    return s;
-//  }
-
+    
 }}} // of namespace classifier, yat, and theplu

trunk/yat/classifier/NCC.h

@@ -28 +28 @@
 
 #include "yat/utility/matrix.h"
+#include "yat/statistics/vector_distance_ptr.h"
 #include "SupervisedClassifier.h"
 
@@ -37 +38 @@
   namespace utlitity {
     class vector;
-  }
-
-  namespace statistics {
-    class Distance;
   }
 
@@ -61 +58 @@
     ///
     /// Constructor taking the training data, the target vector, and
-    /// the distance measure as input.
+    /// the distance measure tag as input.
     ///
-    NCC(const MatrixLookup&, const Target&, const statistics::Distance&);
+    NCC(const MatrixLookup&, const Target&, 
+        const statistics::vector_distance_lookup_weighted_ptr);
     
     ///
     /// Constructor taking the training data with weights, the target
-    /// vector, the distance measure, and a weight matrix for the
-    /// training data as input.
+    /// vector, the distance measure tag.
     ///
-    NCC(const MatrixLookupWeighted&, const Target&, const statistics::Distance&);
+    NCC(const MatrixLookupWeighted&, const Target&, 
+        const statistics::vector_distance_lookup_weighted_ptr);
 
     virtual ~NCC();
@@ -97 +95 @@
     ///
     void predict(const DataLookup2D&, utility::matrix&) const;
-
-
+    
+    
   private:
     utility::matrix centroids_;
-    const statistics::Distance& distance_;                 
+    const statistics::vector_distance_lookup_weighted_ptr distance_;                 
 
     // data_ has to be of type DataLookup2D to accomodate both
     // MatrixLookup and MatrixLookupWeighted
     const DataLookup2D& data_;
-
-    ///
-    /// Calculate the distance to each centroid for a test sample
-    ///
-    void predict(const utility::vector&, const utility::vector&,
-                 utility::vector&) const;
 
   };