Changeset 722 for trunk/yat/classifier

Timestamp:

Dec 27, 2006, 9:49:11 PM (17 years ago)

Author:

Markus Ringnér

Message:

Closes #129

Location:

trunk/yat/classifier

Files:

• EnsembleBuilder.cc (modified) (7 diffs)
• EnsembleBuilder.h (modified) (3 diffs)
• NBC.cc (modified) (1 diff)
• NBC.h (modified) (1 diff)
• NCC.cc (modified) (1 diff)
• NCC.h (modified) (2 diffs)
• SVM.cc (modified) (1 diff)
• SVM.h (modified) (1 diff)
• SupervisedClassifier.h (modified) (2 diffs)

trunk/yat/classifier/EnsembleBuilder.cc

@@ -25 +25 @@
 #include "DataLookup2D.h"
 #include "KernelLookup.h"
+#include "Sampler.h"
 #include "SubsetGenerator.h"
 #include "SupervisedClassifier.h"
@@ -35 +36 @@
 
   EnsembleBuilder::EnsembleBuilder(const SupervisedClassifier& sc, 
-                                   SubsetGenerator& subset) 
-    : mother_(sc), subset_(subset)
+                                   const Sampler& sampler) 
+    : mother_(sc),subset_(new SubsetGenerator(sampler,sc.data()))
   {
   }
@@ -44 +45 @@
     for(size_t i=0; i<classifier_.size(); i++)
       delete classifier_[i];
+    delete subset_;
   }
 
   void EnsembleBuilder::build(void) 
   {
-    for(u_long i=0; i<subset_.size();++i) {
+    for(u_long i=0; i<subset_->size();++i) {
       SupervisedClassifier* classifier=
-        mother_.make_classifier(subset_.training_data(i), 
-                                subset_.training_target(i));
+        mother_.make_classifier(subset_->training_data(i), 
+                                subset_->training_target(i));
       classifier->train();
       classifier_.push_back(classifier);
@@ -75 +77 @@
   {
     result.clear();
-    result.reserve(subset_.target().nof_classes());   
-    for(size_t i=0; i<subset_.target().nof_classes();i++)
+    result.reserve(subset_->target().nof_classes());    
+    for(size_t i=0; i<subset_->target().nof_classes();i++)
       result.push_back(std::vector<statistics::Averager>(data.columns()));
     
@@ -82 +84 @@
     try {
       const KernelLookup& kernel = dynamic_cast<const KernelLookup&>(data);
-      for(u_long k=0;k<subset_.size();k++) {
-        KernelLookup kernel_peter(kernel,subset_.training_index(k),true);
+      for(u_long k=0;k<subset_->size();k++) {
+        KernelLookup kernel_peter(kernel,subset_->training_index(k),true);
         classifier(k).predict(kernel_peter,prediction);
 
@@ -92 +94 @@
     }
     catch (std::bad_cast) {
-      for(u_long k=0;k<subset_.size();k++) {
+      for(u_long k=0;k<subset_->size();k++) {
         classifier(k).predict(data,prediction);
         for(size_t i=0; i<prediction.rows();i++) 
@@ -108 +110 @@
     validation_result_.clear();
 
-    validation_result_.reserve(subset_.target().nof_classes());   
-    for(size_t i=0; i<subset_.target().nof_classes();i++)
-      validation_result_.push_back(std::vector<statistics::Averager>(subset_.target().size()));
+    validation_result_.reserve(subset_->target().nof_classes());    
+    for(size_t i=0; i<subset_->target().nof_classes();i++)
+      validation_result_.push_back(std::vector<statistics::Averager>(subset_->target().size()));
     
     utility::matrix prediction;  
-    for(u_long k=0;k<subset_.size();k++) {
-      classifier(k).predict(subset_.validation_data(k),prediction);
+    for(u_long k=0;k<subset_->size();k++) {
+      classifier(k).predict(subset_->validation_data(k),prediction);
 
       for(size_t i=0; i<prediction.rows();i++) 
         for(size_t j=0; j<prediction.columns();j++) {
-          validation_result_[i][subset_.validation_index(k)[j]].
+          validation_result_[i][subset_->validation_index(k)[j]].
             add(prediction(i,j));
         }           

trunk/yat/classifier/EnsembleBuilder.h

@@ -33 +33 @@
 namespace classifier {  
 
+  class Sampler;
   class SubsetGenerator;
   class DataLookup2D;
@@ -48 +49 @@
     /// Constructor.
     ///
-    EnsembleBuilder(const SupervisedClassifier&, SubsetGenerator&);
+    EnsembleBuilder(const SupervisedClassifier&, const Sampler&);
 
     ///
@@ -90 +91 @@
 
   private:
-  
+    EnsembleBuilder(const EnsembleBuilder&);
+    const EnsembleBuilder& operator=(const EnsembleBuilder&);
+    
+
     const SupervisedClassifier& mother_;
-    SubsetGenerator& subset_;
+    SubsetGenerator* subset_;
     std::vector<SupervisedClassifier*> classifier_;
     std::vector<std::vector<statistics::Averager> > validation_result_;

trunk/yat/classifier/NBC.cc

@@ -51 +51 @@
 
 
+    const DataLookup2D& NBC::data(void) const
+    {
+    return data_;
+    }
+
+
   SupervisedClassifier* 
   NBC::make_classifier(const DataLookup2D& data, const Target& target) const 

trunk/yat/classifier/NBC.h

@@ -60 +60 @@
     virtual ~NBC();
 
+    const DataLookup2D& data(void) const;
+
+
     SupervisedClassifier* make_classifier(const DataLookup2D&, 
                                           const Target&) const;

trunk/yat/classifier/NCC.cc

@@ -64 +64 @@
   }
 
+    const DataLookup2D& NCC::data(void) const
+    {
+    return data_;
+    }
 
   SupervisedClassifier* 

trunk/yat/classifier/NCC.h

@@ -77 +77 @@
     const utility::matrix& centroids(void) const;
 
+    const DataLookup2D& data(void) const;
+
     SupervisedClassifier* make_classifier(const DataLookup2D&, 
                                           const Target&) const;
@@ -98 +100 @@
     utility::matrix centroids_;
     const statistics::Distance& distance_;                 
+
+    // data_ has to be of type DataLookup2D to accomodate both
+    // MatrixLookup and MatrixLookupWeighted
     const DataLookup2D& data_;
 

trunk/yat/classifier/SVM.cc

@@ -98 +98 @@
   }
 
+  const DataLookup2D& SVM::data(void) const
+  {
+    return *kernel_;
+  }
+
+
   double SVM::kernel_mod(const size_t i, const size_t j) const
   {

trunk/yat/classifier/SVM.h

@@ -66 +66 @@
     ///
     virtual ~SVM();
+
+    const DataLookup2D& data(void) const;
 
     ///

trunk/yat/classifier/SupervisedClassifier.h

@@ -59 +59 @@
 
     ///
+    /// @brief Access to the training data 
+    ///
+    virtual const DataLookup2D& data(void) const =0;
+
+
+    ///
     /// An interface for making new classifier objects. This function
     /// allows for specification at run-time of which classifier to
@@ -70 +76 @@
     
 
+
+    ///
+    /// Generate output values for a data set
+    ///
+    virtual void predict(const DataLookup2D&, utility::matrix&) const =0;   
+
+
     ///
     /// Train the classifier.
     ///
     virtual bool train()=0;
-
-    ///
-    /// Generate output values for a data set
-    ///
-    virtual void predict(const DataLookup2D&, utility::matrix&) const =0;