algo::regression::KernelRidge< KERNEL, T > Class Template Reference

Public Member Functions
template<typename... Ts>
	KernelRidge (const arma::Mat< T > &inputs, const arma::Row< T > &labels, const double &lambda, const Ts &... args)
template<typename... Ts>
	KernelRidge (const arma::Mat< T > &inputs, const arma::Row< T > &labels)
template<typename... Ts>
	KernelRidge (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) const
T	ComputeError (const arma::Mat< T > &points, const arma::Row< T > &responses) const
const arma::Row< T > &	Parameters () const
arma::Row< T > &	Parameters ()
double	Lambda () const
double &	Lambda ()
template<typename Archive >
void	serialize (Archive &ar, const unsigned int)

Detailed Description

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

Definition at line 21 of file kernelridge.h.

Constructor & Destructor Documentation

KernelRidge() [1/2]

template<class KERNEL , class T >

template<class... Ts>

algo::regression::KernelRidge< KERNEL, T >::KernelRidge	(	const arma::Mat< T > &	inputs,
		const arma::Row< T > &	labels,
		const double &	lambda,
		const Ts &...	args
	)

Parameters

inputs	X
labels	y
lambda	regularization hyper-parameter
args	for the kernel

Definition at line 20 of file kernelridge_impl.h.

                                                         :
    cov_(args...), lambda_(lambda)
{
  Train(inputs, labels);
}

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

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KernelRidge() [2/2]

template<class KERNEL , class T = DTYPE>

template<typename... Ts>

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

inline

Non-working model

Definition at line 44 of file kernelridge.h.

: cov_(args...), lambda_(0.0) { }

Member Function Documentation

ComputeError()

template<class KERNEL , class T >

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

Calculate the L2 squared error

Parameters

inputs
labels

Definition at line 63 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 T >

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

Parameters

inputs	X*
labels	y*

Definition at line 54 of file kernelridge_impl.h.

{
 
  arma::Mat<T> k_xpx = cov_.GetMatrix(train_inp_,inputs);
  labels = (parameters_ * k_xpx );
}

serialize()

template<class KERNEL , class T = DTYPE>

template<typename Archive >

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

inline

Serialize the model.

Definition at line 81 of file kernelridge.h.

  {
    ar ( cereal::make_nvp("parameters",parameters_),
         cereal::make_nvp("lambda",lambda_),
         cereal::make_nvp("cov",cov_),
         cereal::make_nvp("train_inp",train_inp_));
  }

Train()

template<class KERNEL , class T >

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

Parameters

inputs	X
labels	y

Definition at line 39 of file kernelridge_impl.h.

{
  train_inp_ = inputs;
  
  arma::Mat<T> k_xx = cov_.GetMatrix(train_inp_,train_inp_);
 
  arma::Mat<T> KLambda = k_xx+
       (lambda_ + 1.e-6) * arma::eye<arma::Mat<T>>(k_xx.n_rows, k_xx.n_rows);
 
  parameters_ = 
    arma::conv_to<arma::Row<T>>::from(arma::solve(KLambda, labels.t()));
}

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

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

• kernelridge.h
• kernelridge_impl.h