mlpack::kde::KDERules< MetricType, KernelType, TreeType > Class Template Reference

A dual-tree traversal Rules class for kernel density estimation. More...

#include <kde_rules.hpp>

Public Types
typedef tree::TraversalInfo< TreeType >	TraversalInfoType

Public Member Functions
	KDERules (const arma::mat &referenceSet, const arma::mat &querySet, arma::vec &densities, const double relError, const double absError, const double mcProb, const size_t initialSampleSize, const double mcAccessCoef, const double mcBreakCoef, MetricType &metric, KernelType &kernel, const bool monteCarlo, const bool sameSet)
	Construct KDERules. More...
double	BaseCase (const size_t queryIndex, const size_t referenceIndex)
	Base Case. More...
double	Score (const size_t queryIndex, TreeType &referenceNode)
	SingleTree Rescore. More...
double	Rescore (const size_t queryIndex, TreeType &referenceNode, const double oldScore) const
	SingleTree Score.
double	Score (TreeType &queryNode, TreeType &referenceNode)
	Dual-Tree Score. More...
double	Rescore (TreeType &queryNode, TreeType &referenceNode, const double oldScore) const
	Dual-Tree Rescore. More...
const TraversalInfoType &	TraversalInfo () const
	Get traversal information.
TraversalInfoType &	TraversalInfo ()
	Modify traversal information.
size_t	BaseCases () const
	Get the number of base cases.
size_t	Scores () const
	Get the number of scores.
size_t	MinimumBaseCases () const
	Get the minimum number of base cases we need to perform to have acceptable results. More...

Detailed Description

template<typename MetricType, typename KernelType, typename TreeType>
class mlpack::kde::KDERules< MetricType, KernelType, TreeType >

A dual-tree traversal Rules class for kernel density estimation.

This contains the Score() and BaseCase() implementations.

Constructor & Destructor Documentation

KDERules()

template<typename MetricType , typename KernelType , typename TreeType >

mlpack::kde::KDERules< MetricType, KernelType, TreeType >::KDERules	(	const arma::mat &	referenceSet,
		const arma::mat &	querySet,
		arma::vec &	densities,
		const double	relError,
		const double	absError,
		const double	mcProb,
		const size_t	initialSampleSize,
		const double	mcAccessCoef,
		const double	mcBreakCoef,
		MetricType &	metric,
		KernelType &	kernel,
		const bool	monteCarlo,
		const bool	sameSet
	)

Construct KDERules.

Parameters

referenceSet	Reference set data.
querySet	Query set data.
densities	Vector where estimations will be written.
relError	Relative error tolerance.
absError	Absolute error tolerance.
mcProb	Probability of relative error compliance for Monte Carlo estimations.
initialSampleSize	Initial size of the Monte Carlo samples.
mcAccessCoef	Access coefficient for Monte Carlo estimations.
mcBreakCoef	Break coefficient for Monte Carlo estimations.
metric	Instantiated metric.
kernel	Instantiated kernel.
monteCarlo	If true Monte Carlo estimations will be applied when possible.
sameSet	True if query and reference sets are the same (monochromatic evaluation).

Member Function Documentation

BaseCase()

template<typename MetricType , typename KernelType , typename TreeType >

force_inline double mlpack::kde::KDERules< MetricType, KernelType, TreeType >::BaseCase ( const size_t  queryIndex, const size_t  referenceIndex  )

inline

Base Case.

The base case.

MinimumBaseCases()

template<typename MetricType , typename KernelType , typename TreeType >

size_t mlpack::kde::KDERules< MetricType, KernelType, TreeType >::MinimumBaseCases ( ) const

inline

Get the minimum number of base cases we need to perform to have acceptable results.

Rescore()

template<typename MetricType , typename KernelType , typename TreeType >

force_inline double mlpack::kde::KDERules< MetricType, KernelType, TreeType >::Rescore ( TreeType &  queryNode, TreeType &  referenceNode, const double  oldScore  ) const

inline

Dual-Tree Rescore.

Dual-tree rescore.

Score() [1/2]

template<typename MetricType , typename KernelType , typename TreeType >

double mlpack::kde::KDERules< MetricType, KernelType, TreeType >::Score ( const size_t  queryIndex, TreeType &  referenceNode  )

inline

SingleTree Rescore.

Single-tree scoring function.

Score() [2/2]

template<typename MetricType , typename KernelType , typename TreeType >

double mlpack::kde::KDERules< MetricType, KernelType, TreeType >::Score ( TreeType &  queryNode, TreeType &  referenceNode  )

inline

Dual-Tree Score.

Dual-tree scoring function.

---

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

• src/mlpack/methods/kde/kde_rules.hpp
• src/mlpack/methods/kde/kde_rules_impl.hpp