Impala Documentation

Matrix::Mat* Impala::Core::Training::PrecomputeKernelMatrix	(	std::vector< Feature::FeatureTable * >	features,
		std::vector< double >	weights,
		Util::PropertySet *	properties
	)

Definition at line 19 of file PrecomputeKernelMatrix.h.

References Impala::Core::Vector::Apply(), Chi2Distance(), Impala::Core::Array::Array2dTem< StorT, elemSize, ArithT >::H(), ILOG_ERROR, ILOG_VAR, Impala::Core::Array::Pattern::PatMPixOp(), Impala::Core::Array::PixSum(), and Impala::Core::Array::Array2dTem< StorT, elemSize, ArithT >::W().

Referenced by PrecomputeKernelMatrix().

00022 {
00023     ILOG_VAR(Training.PrecomputeKernelMatrix);
00024     if(!(weights.size() == features.size()))
00025     {
00026         ILOG_ERROR("size of list does not match!");
00027         return 0;
00028     }
00029 
00030     std::vector<Matrix::Mat*> DistanceMatrices;
00031     std::vector<double> AList;
00032     // perhaps we should make this a pattern?
00033     std::vector<Feature::FeatureTable*>::iterator it;
00034     for(it=features.begin() ; it!=features.end() ; ++it)
00035     {
00036         Feature::FeatureTable* f = *it;
00037 
00038         // fill a matrix with chi2 distance
00039         Matrix::Mat* m = Apply(&Training::Chi2Distance, f->GetColumn2(), f->GetColumn2());
00040         DistanceMatrices.push_back(m);
00041 
00042         // get A (average of all weights)
00043         double a = Array::PixSum(m);
00044         a /= m->W() * m->H();
00045         AList.push_back(a);
00046     }
00047 
00048     if(!(weights.size() == AList.size() == DistanceMatrices.size()))
00049     {
00050         ILOG_ERROR("size of list does not match!");
00051         return 0;
00052     }
00053     // fill matrix with K(vi,vj)
00054     MpoChi2Kernel kernel(weights, AList);
00055     Array::Pattern::PatMPixOp(DistanceMatrices[0], DistanceMatrices, kernel);
00056 
00057     for(int i=1 ; i<DistanceMatrices.size() ; ++i)
00058         delete DistanceMatrices[i];
00059     return DistanceMatrices[0];
00060 }

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