28 virtual void train()
override;
42 std::vector<std::vector<unsigned int>> &
_tuple;
51 std::vector<std::unique_ptr<const PolynomialQuadrature::Polynomial>> &
_poly;
A class used to produce samples based on quadrature for Polynomial Chaos.
unsigned int _rtype
The method in which to perform the regression (0=integration, 1=OLS)
std::size_t & _ncoeff
Total number of coefficient (defined by size of _tuple)
const Real & _ridge_penalty
The penalty parameter for Ridge regularization.
std::vector< std::vector< unsigned int > > & _tuple
A _ndim-by-_ncoeff matrix containing the appropriate one-dimensional polynomial order.
virtual void train() override
const unsigned int & _order
Maximum polynomial order. The sum of 1D polynomial orders does not go above this value.
static InputParameters validParams()
std::vector< std::unique_ptr< const PolynomialQuadrature::Polynomial > > & _poly
The distributions used for sampling.
QuadratureSampler * _quad_sampler
QuadratureSampler pointer, necessary for applying quadrature weights.
const std::vector< Real > & _predictor_row
Predictor values.
StochasticTools::Calculator< std::vector< Real >, Real > RealCalculator
virtual void postTrain() override
DIE A HORRIBLE DEATH HERE typedef LIBMESH_DEFAULT_SCALAR_TYPE Real
This is the main trainer base class.
std::vector< Real > & _coeff
These are the coefficients we are after in the PC expansion.
DenseMatrix< Real > _matrix
const InputParameters & parameters() const
unsigned int & _ndim
Total number of parameters/dimensions.
std::vector< std::unique_ptr< RealCalculator > > _calculators
Calculators used for standardization in linear regression.
PolynomialChaosTrainer(const InputParameters ¶meters)
virtual void preTrain() override