algo::regression::SemiParamKernelRidge< KERNEL, FUNC, T > Class Template Reference

Public Member Functions
template<class... Ts>
	SemiParamKernelRidge (const arma::Mat< T > &inputs, const arma::Row< T > &labels, const T lambda, const size_t num_funcs, const Ts &... args)
template<class... Ts>
	SemiParamKernelRidge (const arma::Mat< T > &inputs, const arma::Row< T > &labels, const T lambda, const T perc, const Ts &... args)
template<typename... Ts>
	SemiParamKernelRidge (const Ts &... args)
void	Train (const arma::Mat< T > &inputs, const arma::Row< T > &labels)
void	Predict (const arma::Mat< T > &inputs, arma::Row< T > &labels)
T	ComputeError (const arma::Mat< T > &points, const arma::Row< T > &responses)
const arma::Row< T > &	Parameters () const
arma::Row< T > &	Parameters ()
T	Lambda () const
T &	Lambda ()
template<typename Archive >
void	serialize (Archive &ar, const unsigned int)

Detailed Description

template<class KERNEL, class FUNC, class T = DTYPE>
class algo::regression::SemiParamKernelRidge< KERNEL, FUNC, T >

Definition at line 166 of file kernelridge.h.

Constructor & Destructor Documentation

SemiParamKernelRidge() [1/2]

template<class KERNEL , class FUNC , class T >

template<class... Ts>

algo::regression::SemiParamKernelRidge< KERNEL, FUNC, T >::SemiParamKernelRidge	(	const arma::Mat< T > &	inputs,
		const arma::Row< T > &	labels,
		const T	lambda,
		const size_t	num_funcs,
		const Ts &...	args
	)

Parameters

inputs	: X
labels	: y
lambda	: regularization hyper-parameter
num_funcs	: number of \psi
args	: for the kernel hyper-parameters

Definition at line 130 of file kernelridge_impl.h.

                                           :
    cov_(args...), lambda_(lambda), M_(num_funcs), perc_(0.), func_(num_funcs)
{
  Train(inputs, labels);
}

References algo::regression::SemiParamKernelRidge< KERNEL, FUNC, T >::Train().

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SemiParamKernelRidge() [2/2]

template<class KERNEL , class FUNC , class T = DTYPE>

template<typename... Ts>

algo::regression::SemiParamKernelRidge< KERNEL, FUNC, T >::SemiParamKernelRidge ( const Ts &...  args )

inline

Non-working model

Definition at line 193 of file kernelridge.h.

                                             : cov_(args...),
                                               lambda_(0.0),
                                               M_(size_t(0)),
                                               perc_(T(0)),
                                               func_(size_t(0))  { }

Member Function Documentation

ComputeError()

template<class KERNEL , class FUNC , class T >

T algo::regression::SemiParamKernelRidge< KERNEL, FUNC, T >::ComputeError	(	const arma::Mat< T > &	points,
		const arma::Row< T > &	responses
	)

Calculate the L2 squared error

Parameters

inputs
labels

Definition at line 199 of file kernelridge_impl.h.

{
  arma::Row<T> temp;
  Predict(inputs, temp);
  const size_t n_points = inputs.n_cols;
 
  temp = labels - temp;
 
  const T cost = (arma::dot(temp, temp) / n_points);
 
  return cost;
}

Predict()

template<class KERNEL , class FUNC , class T >

void algo::regression::SemiParamKernelRidge< KERNEL, FUNC, T >::Predict	(	const arma::Mat< T > &	inputs,
		arma::Row< T > &	labels
	)

Parameters

inputs	X*
labels	y*

Definition at line 189 of file kernelridge_impl.h.

{
  arma::Mat<T> K = cov_.GetMatrix(inputs,train_inp_);
  arma::Mat<T> psi = func_.Predict(inputs);
  arma::Mat<T> A = arma::join_rows(K, psi.t()); 
  labels = (A * parameters_.t()).t() + func_.Mean(inputs);
}

serialize()

template<class KERNEL , class FUNC , class T = DTYPE>

template<typename Archive >

void algo::regression::SemiParamKernelRidge< KERNEL, FUNC, T >::serialize ( Archive &  ar, const unsigned int    )

inline

Serialize the model.

Definition at line 232 of file kernelridge.h.

  {
    ar (  cereal::make_nvp("parameters",parameters_),
          cereal::make_nvp("M",M_),
          cereal::make_nvp("N",N_),
          cereal::make_nvp("lambda",lambda_),
          cereal::make_nvp("cov",cov_),
          cereal::make_nvp("func",func_),
          cereal::make_nvp("perc",perc_),
          cereal::make_nvp("train_inp",train_inp_) );
  }

Train()

template<class KERNEL , class FUNC , class T >

void algo::regression::SemiParamKernelRidge< KERNEL, FUNC, T >::Train	(	const arma::Mat< T > &	inputs,
		const arma::Row< T > &	labels
	)

Parameters

inputs	X
labels	y

Definition at line 161 of file kernelridge_impl.h.

{
  train_inp_ = inputs;
  N_ = train_inp_.n_cols;
 
  psi_ = func_.Predict(inputs); 
 
  if (M_ == 0)
    M_ = func_.GetM();
 
  arma::Mat<T> k_xx = cov_.GetMatrix(train_inp_,train_inp_);
 
  arma::Mat<T> K = k_xx +
       (1.e-8) * arma::eye<arma::Mat<T>>(k_xx.n_rows, k_xx.n_rows);
  
  arma::Mat<T> A = arma::join_rows(K, psi_.t()); 
  arma::Mat<T> B = arma::join_cols(arma::join_rows(K,
                                arma::zeros<arma::Mat<T>>(N_,M_)),
                                arma::zeros<arma::Mat<T>>(M_,N_+M_)); 
 
  parameters_ = arma::conv_to<arma::Row<T>>::from(
    arma::solve(A.t() * A + lambda_ * B.t(), A.t() * (labels.t()-
                                                      func_.Mean(inputs).t())));
  
}

Referenced by algo::regression::SemiParamKernelRidge< KERNEL, FUNC, T >::SemiParamKernelRidge().

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The documentation for this class was generated from the following files:

• kernelridge.h
• kernelridge_impl.h