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// -*- Mode: C++; tab-width: 2; -*-
// vi: set ts=2:
//
//
#include <BALL/QSAR/rrModel.h>
//#include <BALL/SYSTEM/timer.h>
#include <Eigen/Dense>
namespace BALL
{
namespace QSAR
{
RRModel::RRModel(const QSARData& q, double lambda) : MLRModel(q)
{
type_="RR";
lambda_ = lambda;
}
RRModel::~RRModel()
{
}
void RRModel::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 (lambda_ == 0 && 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_;
if (lambda_ != 0)
{
Eigen::MatrixXd I(m.rows(), m.rows());
I.setIdentity();
I *= lambda_;
m += I;
}
try
{
// Timer timer; timer.start();
training_result_ = m.colPivHouseholderQr().solve(descriptor_matrix_.transpose()*Y_);
// timer.stop(); cout<<timer.getClockTime()<<endl;
// timer.start();
// Matrix X1 = m;
// Matrix Y1 = descriptor_matrix_.t()*Y_;
// UpperTriangularMatrix U; Matrix M;
// QRZ(X1, U); QRZ(X1, Y1, M); // Y1 now contains resids
// Matrix test = U.i() * M;
// timer.stop(); cout<<timer.getClockTime()<<endl;
//
// cout<<(training_result_-test).t()<<endl;
}
catch(BALL::Exception::GeneralException e)
{
training_result_.resize(0, 0);
throw Exception::SingularMatrixError(__FILE__, __LINE__, "Matrix for RR training is singular!! Check that descriptor_matrix_ does not contain empty columns and that lambda is not too small!");
return;
}
calculateOffsets();
}
void RRModel::setParameters(vector<double>& v)
{
if (v.size() != 1)
{
String c = "Wrong number of model parameters! Needed: 1;";
c = c+" given: "+String(v.size());
throw Exception::ModelParameterError(__FILE__, __LINE__, c.c_str());
}
lambda_ = v[0];
}
vector<double> RRModel::getParameters() const
{
vector<double> d;
d.push_back(lambda_);
return d;
}
}
}
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