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

Public Member Functions
template<typename... Ts>
	Kernel (const arma::Mat< T > &inputs, const arma::Row< T > &labels, const Ts &... args)
template<typename... Ts>
	Kernel (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
template<typename Archive >
void	serialize (Archive &ar, const unsigned int)

Detailed Description

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

Definition at line 101 of file kernelridge.h.

Constructor & Destructor Documentation

Kernel() [1/2]

template<class KERNEL , class T >

template<class... Ts>

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

Parameters

inputs	X
labels	y
args	for the kernel

Definition at line 82 of file kernelridge_impl.h.

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

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

Here is the call graph for this function:

Kernel() [2/2]

template<class KERNEL , class T = DTYPE>

template<typename... Ts>

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

inline

Non-working model

Definition at line 119 of file kernelridge.h.

: cov_(args...){ }

Member Function Documentation

ComputeError()

template<class KERNEL , class T >

T algo::regression::Kernel< 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 111 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::Kernel< KERNEL, T >::Predict	(	const arma::Mat< T > &	inputs,
		arma::Row< T > &	labels
	)		const

Parameters

inputs	X*
labels	y*

Definition at line 98 of file kernelridge_impl.h.

{
  arma::Mat<T> sim = cov_.GetMatrix(train_inp_, inputs);
  const size_t N = sim.n_rows;
  for(size_t i=0; i<N; i++)
  {
    sim.row(i) /= arma::sum(sim,0);  
  }
  labels = train_lab_ * sim;
}

serialize()

template<class KERNEL , class T = DTYPE>

template<typename Archive >

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

inline

Serialize the model.

Definition at line 149 of file kernelridge.h.

  {
    ar (cereal::make_nvp("train_inp",train_inp_),
        cereal::make_nvp("train_lab",train_lab_),
        cereal::make_nvp("cov",cov_));
  }

Train()

template<class KERNEL , class T >

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

Parameters

inputs	X
labels	y
args	for the kernel

Definition at line 90 of file kernelridge_impl.h.

{
  train_inp_ = inputs;
  train_lab_ = labels;
}

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

Here is the caller graph for this function:

---

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

• kernelridge.h
• kernelridge_impl.h