Changeset 1954 for trunk/yat/classifier/EnsembleBuilder.h

Timestamp:

May 7, 2009, 5:30:58 PM (14 years ago)

Author:

Jari Häkkinen

Message:

Merged patch release 0.5.3 to the trunk. Delta 0.5.3 - 0.5.2

File:

• trunk/yat/classifier/EnsembleBuilder.h (modified) (11 diffs)

trunk/yat/classifier/EnsembleBuilder.h

@@ -9 +9 @@
   Copyright (C) 2007 Jari Häkkinen, Peter Johansson
   Copyright (C) 2008 Jari Häkkinen, Peter Johansson, Markus Ringnér
+  Copyright (C) 2009 Jari Häkkinen
 
   This file is part of the yat library, http://dev.thep.lu.se/yat
@@ -128 +129 @@
   // implementation
 
-  template <class C, class D> 
-  EnsembleBuilder<C,D>::EnsembleBuilder(const C& sc, const D& data,
-                                        const Sampler& sampler) 
-    : mother_(sc),subset_(new SubsetGenerator<D>(sampler,data))
-  {
-  }
-
-
-  template <class C, class D> 
-  EnsembleBuilder<C, D>::EnsembleBuilder(const C& sc, const D& data, 
-                                         const Sampler& sampler,
-                                         FeatureSelector& fs) 
+  template <class Classifier, class Data>
+  EnsembleBuilder<Classifier, Data>::EnsembleBuilder(const Classifier& sc,
+                                                     const Data& data,
+                                                     const Sampler& sampler)
+    : mother_(sc),subset_(new SubsetGenerator<Data>(sampler,data))
+  {
+  }
+
+
+  template <class Classifier, class Data>
+  EnsembleBuilder<Classifier, Data>::EnsembleBuilder(const Classifier& sc,
+                                                     const Data& data,
+                                                     const Sampler& sampler,
+                                                     FeatureSelector& fs)
     : mother_(sc),
-      subset_(new SubsetGenerator<D>(sampler,data,fs))
-  {
-  }
-
-
-  template <class C, class D> 
-  EnsembleBuilder<C, D>::~EnsembleBuilder(void) 
+      subset_(new SubsetGenerator<Data>(sampler,data,fs))
+  {
+  }
+
+
+  template <class Classifier, class Data>
+  EnsembleBuilder<Classifier, Data>::~EnsembleBuilder(void)
   {
     for(size_t i=0; i<classifier_.size(); i++)
@@ -155 +158 @@
 
 
-  template <class C, class D> 
-  void EnsembleBuilder<C, D>::build(void) 
+  template <class Classifier, class Data>
+  void EnsembleBuilder<Classifier, Data>::build(void)
   {
     if (classifier_.empty()){
       for(unsigned long i=0; i<subset_->size();++i) {
-        C* classifier = mother_.make_classifier();
+        Classifier* classifier = mother_.make_classifier();
         classifier->train(subset_->training_data(i), 
                           subset_->training_target(i));
@@ -169 +172 @@
 
 
-  template <class C, class D> 
-  const C& EnsembleBuilder<C, D>::classifier(size_t i) const
+  template <class Classifier, class Data>
+  const Classifier& EnsembleBuilder<Classifier, Data>::classifier(size_t i) const
   {
     return *(classifier_[i]);
@@ -176 +179 @@
 
 
-  template <class C, class D> 
-  void EnsembleBuilder<C, D>::predict
-  (const D& data, std::vector<std::vector<statistics::Averager> >& result)
+  template <class Classifier, class Data>
+  void EnsembleBuilder<Classifier, Data>::predict
+  (const Data& data, std::vector<std::vector<statistics::Averager> >& result)
   {
     result = std::vector<std::vector<statistics::Averager> >
@@ -187 +190 @@
 
     for(unsigned long k=0;k<size();++k) {       
-      D sub_data =  test_data(data, k);
+      Data sub_data = test_data(data, k);
       classifier(k).predict(sub_data,prediction);
     }
@@ -197 +200 @@
 
   
-  template <class C, class D> 
-  unsigned long EnsembleBuilder<C, D>::size(void) const
+  template <class Classifier, class Data>
+  unsigned long EnsembleBuilder<Classifier, Data>::size(void) const
   {
     return classifier_.size();
@@ -204 +207 @@
 
 
-  template <class C, class D> 
-  MatrixLookup EnsembleBuilder<C, D>::test_data(const MatrixLookup& data, 
+  template <class Classifier, class Data>
+  MatrixLookup EnsembleBuilder<Classifier,
+                               Data>::test_data(const MatrixLookup& data,
                                                 size_t k)
   {
@@ -212 +216 @@
   
 
-  template <class C, class D> 
+  template <class Classifier, class Data>
   MatrixLookupWeighted 
-  EnsembleBuilder<C, D>::test_data(const MatrixLookupWeighted& data, size_t k)
+  EnsembleBuilder<Classifier, Data>::test_data(const MatrixLookupWeighted& data,
+                                               size_t k)
   {
     return MatrixLookupWeighted(data, subset_->training_features(k), true);
@@ -220 +225 @@
   
 
-  template <class C, class D> 
+  template <class Classifier, class Data>
   KernelLookup
-  EnsembleBuilder<C, D>::test_data(const KernelLookup& kernel, size_t k)
+  EnsembleBuilder<Classifier, Data>::test_data(const KernelLookup& kernel,
+                                               size_t k)
   {
     // weighted case
@@ -245 +251 @@
   
 
-  template <class C, class D> 
+  template <class Classifier, class Data>
   const std::vector<std::vector<statistics::Averager> >& 
-  EnsembleBuilder<C, D>::validate(void)
+  EnsembleBuilder<Classifier, Data>::validate(void)
   {
     // Don't recalculate validation_result_