Changeset 1050 for trunk/yat/classifier
- Timestamp:
- Feb 7, 2008, 7:47:34 PM (15 years ago)
- Location:
- trunk/yat/classifier
- Files:
-
- 3 edited
Legend:
- Unmodified
- Added
- Removed
-
trunk/yat/classifier/IGP.h
r1031 r1050 30 30 #include "yat/utility/vector.h" 31 31 #include "yat/utility/yat_assert.h" 32 #include "yat/statistics/distance.h"33 32 34 33 #include <cmath> … … 71 70 private: 72 71 utility::vector igp_; 72 Distance distance_; 73 73 74 74 const MatrixLookup& matrix_; … … 94 94 for(u_int j=0; j<target_.size(); j++) { 95 95 DataLookup1D b(matrix_,j,false); 96 double dist=statistics:: 97 distance(a.begin,a.end(),b.begin(), 98 statistics::distance_traits<Distance>::distace()); 96 double dist=distance_(a.begin, a.end(), b.begin()); 99 97 if(j!=i && dist<mindist) { 100 98 mindist=dist; -
trunk/yat/classifier/KNN.h
r1042 r1050 25 25 */ 26 26 27 #include "DataLookup1D.h" 27 28 #include "DataLookupWeighted1D.h" 28 29 #include "MatrixLookup.h" … … 30 31 #include "SupervisedClassifier.h" 31 32 #include "Target.h" 32 #include "yat/statistics/distance.h"33 33 #include "yat/utility/matrix.h" 34 34 #include "yat/utility/yat_assert.h" … … 113 113 u_int k_; 114 114 115 Distance distance_; 115 116 /// 116 117 /// Calculates the distances between a data set and the training … … 156 157 for(size_t j=0; j<test.columns(); j++) { 157 158 classifier::DataLookup1D test(*test_unweighted,j,false); 158 (*distances)(i,j) = 159 statistics::distance(classifier::DataLookup1D(data_, 160 i,false).begin(), 161 classifier::DataLookup1D(data_, 162 i,false).end(), 163 test.begin(), 164 typename statistics:: 165 distance_traits<Distance>::distance()); 159 classifier::DataLookup1D tmp(data_,i,false); 160 (*distances)(i,j) = distance_(tmp.begin(), tmp.end(), test.begin()); 166 161 utility::yat_assert<std::runtime_error>(!std::isnan((*distances)(i,j))); 167 162 } … … 180 175 classifier::DataLookupWeighted1D test(*test_weighted,j,false); 181 176 utility::yat_assert<std::runtime_error>(training.size()==test.size()); 182 (*distances)(i,j) = 183 statistics::distance(training.begin(),training.end(), 184 test.begin(), typename statistics::distance_traits<Distance>::distance()); 177 (*distances)(i,j) = distance_(training.begin(), training.end(), 178 test.begin()); 185 179 utility::yat_assert<std::runtime_error>(!std::isnan((*distances)(i,j))); 186 180 } -
trunk/yat/classifier/NCC.h
r1042 r1050 37 37 #include "yat/statistics/Averager.h" 38 38 #include "yat/statistics/AveragerWeighted.h" 39 #include "yat/statistics/distance.h"40 41 39 #include "yat/utility/Iterator.h" 42 40 #include "yat/utility/IteratorWeighted.h" … … 112 110 utility::matrix* centroids_; 113 111 bool centroids_nan_; 112 Distance distance_; 114 113 115 114 // data_ has to be of type DataLookup2D to accomodate both … … 270 269 DataLookup1D centroid(unweighted_centroids,k,false); 271 270 utility::yat_assert<std::runtime_error>(in.size()==centroid.size()); 272 prediction(k,j)=statistics:: 273 distance(in.begin(),in.end(),centroid.begin(), 274 typename statistics::distance_traits<Distance>::distance()); 271 prediction(k,j) = distance_(in.begin(), in.end(), centroid.begin()); 275 272 } 276 273 } … … 287 284 DataLookupWeighted1D centroid(weighted_centroids,k,false); 288 285 utility::yat_assert<std::runtime_error>(in.size()==centroid.size()); 289 prediction(k,j)=statistics:: 290 distance(in.begin(),in.end(),centroid.begin(), 291 typename statistics::distance_traits<Distance>::distance()); 286 prediction(k,j) = distance_(in.begin(), in.end(), centroid.begin()); 292 287 } 293 288 }
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