mlpack::metric::IPMetric< KernelType > Class Template Reference

The inner product metric, IPMetric, takes a given Mercer kernel (KernelType), and when Evaluate() is called, returns the distance between the two points in kernel space: More...

Inheritance diagram for mlpack::metric::IPMetric< KernelType >:

Public Member Functions
	IPMetric ()
	Create the IPMetric without an instantiated kernel. More...
	IPMetric (KernelType &kernel)
	Create the IPMetric with an instantiated kernel. More...
	~IPMetric ()
	Destroy the IPMetric object. More...
template<typename VecTypeA , typename VecTypeB >
VecTypeA::elem_type	Evaluate (const VecTypeA &a, const VecTypeB &b)
	Evaluate the metric. More...
const KernelType &	Kernel () const
	Get the kernel. More...
KernelType &	Kernel ()
	Modify the kernel. More...
template<typename Archive >
void	Serialize (Archive &ar, const unsigned int version)
	Serialize the metric. More...

Private Attributes
KernelType *	kernel
	The kernel we are using. More...
bool	kernelOwner
	If true, we are responsible for deleting the kernel. More...

Detailed Description

template<typename KernelType>
class mlpack::metric::IPMetric< KernelType >

The inner product metric, IPMetric, takes a given Mercer kernel (KernelType), and when Evaluate() is called, returns the distance between the two points in kernel space:

Template Parameters

KernelType

Type of Kernel to use. This must be a Mercer kernel (positive definite), otherwise the metric may not be valid.

Definition at line 32 of file ip_metric.hpp.

Constructor & Destructor Documentation

template<typename KernelType>

mlpack::metric::IPMetric< KernelType >::IPMetric

(

)

Create the IPMetric without an instantiated kernel.

template<typename KernelType>

mlpack::metric::IPMetric< KernelType >::IPMetric

(

KernelType &

kernel

)

Create the IPMetric with an instantiated kernel.

template<typename KernelType>

mlpack::metric::IPMetric< KernelType >::~IPMetric

(

)

Destroy the IPMetric object.

Member Function Documentation

template<typename KernelType>

template<typename VecTypeA , typename VecTypeB >

VecTypeA::elem_type mlpack::metric::IPMetric< KernelType >::Evaluate	(	const VecTypeA &	a,
		const VecTypeB &	b
	)

Evaluate the metric.

Template Parameters

VecTypeA	Type of first vector.
VecTypeB	Type of second vector.

Parameters

a	First vector.
b	Second vector.

Returns

Distance between the two points in kernel space.

template<typename KernelType>

const KernelType& mlpack::metric::IPMetric< KernelType >::Kernel ( ) const

inline

Get the kernel.

Definition at line 57 of file ip_metric.hpp.

template<typename KernelType>

KernelType& mlpack::metric::IPMetric< KernelType >::Kernel ( )

inline

Modify the kernel.

Definition at line 59 of file ip_metric.hpp.

template<typename KernelType>

template<typename Archive >

void mlpack::metric::IPMetric< KernelType >::Serialize	(	Archive &	ar,
		const unsigned int	version
	)

Serialize the metric.

Referenced by mlpack::metric::IPMetric< kernel::EpanechnikovKernel >::Kernel().

Member Data Documentation

template<typename KernelType>

KernelType* mlpack::metric::IPMetric< KernelType >::kernel

private

The kernel we are using.

Definition at line 67 of file ip_metric.hpp.

Referenced by mlpack::metric::IPMetric< kernel::EpanechnikovKernel >::Kernel().

template<typename KernelType>

bool mlpack::metric::IPMetric< KernelType >::kernelOwner

private

If true, we are responsible for deleting the kernel.

Definition at line 69 of file ip_metric.hpp.

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

• src/mlpack/core/metrics/ip_metric.hpp