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// -*- Mode: C++; tab-width: 2; -*-
// vi: set ts=2:
//
//
#include <BALL/QSAR/linearModel.h>
namespace BALL
{
namespace QSAR
{
LinearModel::LinearModel(const QSARData& q) : RegressionModel(q) {}
LinearModel::~LinearModel()
{
}
void LinearModel::operator = (const LinearModel& m)
{
RegressionModel::operator = (m);
validation->setCoefficientStdErrors(m.validation->getCoefficientStdErrors());
}
void LinearModel::calculateOffsets()
{
offsets_ = ((descriptor_matrix_*training_result_)-Y_).colwise().sum() / training_result_.rows();
//cout<<"offset : "<<offsets_(1)<<endl<<flush;
}
Eigen::VectorXd LinearModel::predict(const vector<double> & substance, bool transform)
{
if (training_result_.rows() == 0)
{
throw Exception::InconsistentUsage(__FILE__, __LINE__, "Model must be trained before it can predict the activitiy of substances!");
}
Eigen::VectorXd v = getSubstanceVector(substance, transform);
Eigen::VectorXd res = v.transpose()*training_result_;
//if (offsets_.getSize() == res.getSize()) res -= offsets_;
if (transform && y_transformations_.cols() != 0)
{
backTransformPrediction(res);
}
return res;
}
}
}
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