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// -*- Mode: C++; tab-width: 2; -*-
// vi: set ts=2:
//
//
#include <BALL/QSAR/mlrModel.h>
#include <Eigen/Dense>
namespace BALL
{
namespace QSAR
{
MLRModel::MLRModel(const QSARData& q) : LinearModel(q)
{
type_="MLR";
}
MLRModel::~MLRModel()
{
}
void MLRModel::train()
{
if (descriptor_matrix_.cols() == 0)
{
throw Exception::InconsistentUsage(__FILE__, __LINE__, "Data must be read into the model before training!");
}
if (Y_.cols() == 0)
{
throw Exception::InconsistentUsage(__FILE__, __LINE__, "No response values have been read! Model can not be trained!");
}
if (descriptor_matrix_.cols() >= descriptor_matrix_.rows())
{
throw Exception::SingularMatrixError(__FILE__, __LINE__, "For MLR model, matrix must have more rows than columns in order to be invertible!!");
//training_result_.ReSize(0, 0);
//return;
}
Eigen::MatrixXd m = descriptor_matrix_.transpose()*descriptor_matrix_;
try
{
training_result_ = m.colPivHouseholderQr().solve(descriptor_matrix_.transpose()*Y_);
}
catch(BALL::Exception::GeneralException e)
{
training_result_.resize(0, 0);
throw Exception::SingularMatrixError(__FILE__, __LINE__, "Matrix for MLR training is singular!! Check that descriptor_matrix_ does not contain empty columns!");
return;
}
calculateOffsets();
}
}
}
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