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 IPMetric< KernelType >:

[legend]

Public Member Functions
	IPMetric ()
	Create the IPMetric without an instantiated kernel. More...

	IPMetric (KernelType &kernel)
	Create the IPMetric with an instantiated kernel. More...

	IPMetric (const IPMetric &other)
	Copy the parameters of the given metric. 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...

IPMetric &	operator= (const IPMetric &other)
	Assign this metric to be a copy of the given metric. More...

template < typename Archive >
void	serialize (Archive &ar, const uint32_t version)
	Serialize the metric. 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:

$d(x, y) = \sqrt{ K(x, x) + K(y, y) - 2K(x, y) }.$

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

◆ IPMetric() [1/3]

IPMetric ( )

Create the IPMetric without an instantiated kernel.

◆ IPMetric() [2/3]

IPMetric ( KernelType & kernel )

Create the IPMetric with an instantiated kernel.

◆ ~IPMetric()

~IPMetric ( )

Destroy the IPMetric object.

◆ IPMetric() [3/3]

IPMetric ( const IPMetric< KernelType > & other )

Copy the parameters of the given metric.

Member Function Documentation

◆ Evaluate()

VecTypeA::elem_type 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.

◆ Kernel() [1/2]

const KernelType& Kernel ( ) const

inline

Get the kernel.

Definition at line 63 of file ip_metric.hpp.

◆ Kernel() [2/2]

KernelType& Kernel ( )

inline

Modify the kernel.

Definition at line 65 of file ip_metric.hpp.

◆ operator=()

IPMetric& operator= ( const IPMetric< KernelType > & other )

Assign this metric to be a copy of the given metric.

◆ serialize()

void serialize	(	Archive &	ar,
		const uint32_t	version
	)

Serialize the metric.

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

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

/home/ryan/src/mlpack.org/_src/mlpack-git/src/mlpack/core/metrics/ip_metric.hpp

Public Member Functions