This class implements one cluster that holds the mean values of all observations belonging to this cluster and the indices of all observations belonging to this cluster. More...

#include <ClusteringKMeans.h>

Public Member Functions
	Cluster (Cluster &&cluster) noexcept
	Move constructor for another cluster object.

const Observation &	mean () const
	Returns the mean observation value of this cluster.

const DataIndices &	dataIndices () const
	Returns the indices of the observations that belong to this cluster.

TSquareDistance	sqrDistance (const Observation &observation) const
	Returns the square distance between a given observation and this cluster (the mean observation value of this cluster).

TSquareDistance	maximalSqrDistance (DataIndex *observationIndex=nullptr) const
	Calculates the maximal square distance between the mean observation value of this cluster and all observations which belong to this cluster.

TSquareDistance	averageSqrDistance () const
	Calculates the average square distance between the mean observation value of this cluster and all observations which belong to this cluster.

Cluster &	operator= (Cluster &&cluster) noexcept
	Move operator moving a cluster object to this object.

bool	operator< (const Cluster &cluster) const
	Returns whether the left cluster has less elements than the right cluster.

Protected Member Functions
	Cluster (const ClusteringKMeans< T, tDimension, TSum, TSquareDistance, tUseIndices > &owner, const Observation &mean)
	Creates a new cluster object by a given mean value.

	Cluster (const ClusteringKMeans< T, tDimension, TSum, TSquareDistance, tUseIndices > &owner, const Observation &mean, const DataIndices &dataIndices)
	Creates a new cluster object by a given mean value and several indices of observations that belong to this cluster.

	Cluster (const ClusteringKMeans< T, tDimension, TSum, TSquareDistance, tUseIndices > &owner, const Observation &mean, DataIndices &&dataIndices)
	Creates a new cluster object by a given mean value and several indices of observations that belong to this cluster.

DataIndices &	dataIndices ()
	Returns the data-indices of the observations that belong to this cluster.

void	updateMean ()
	Updates the mean observation value of this cluster by application of the stored indices of all observations that belong to this cluster.

Protected Attributes
const ClusteringKMeans< T, tDimension, TSum, TSquareDistance, tUseIndices > *	owner_
	The owner of this cluster.

Observation	mean_
	The mean observation value of this cluster.

DataIndices	dataIndices_
	The data indices of all observation that belong to this cluster.

Friends
class	ClusteringKMeans< T, tDimension, TSum, TSquareDistance, tUseIndices >

class	std::allocator< Cluster >

Detailed Description

template<typename T, size_t tDimension, typename TSum = T, typename TSquareDistance = T, bool tUseIndices = true>
class Ocean::ClusteringKMeans< T, tDimension, TSum, TSquareDistance, tUseIndices >::Cluster

This class implements one cluster that holds the mean values of all observations belonging to this cluster and the indices of all observations belonging to this cluster.

Constructor & Destructor Documentation

◆ Cluster() [1/4]

template<typename T , size_t tDimension, typename TSum , typename TSquareDistance , bool tUseIndices>

Ocean::ClusteringKMeans< T, tDimension, TSum, TSquareDistance, tUseIndices >::Cluster::Cluster ( Cluster && cluster )

inlinenoexcept

Move constructor for another cluster object.

Parameters

cluster The cluster object to be moved

◆ Cluster() [2/4]

template<typename T , size_t tDimension, typename TSum , typename TSquareDistance , bool tUseIndices>

Ocean::ClusteringKMeans< T, tDimension, TSum, TSquareDistance, tUseIndices >::Cluster::Cluster	(	const ClusteringKMeans< T, tDimension, TSum, TSquareDistance, tUseIndices > &	owner,
		const Observation &	mean
	)

inlineprotected

Creates a new cluster object by a given mean value.

Parameters

owner	The owner of this cluster object
mean	The mean observation value that will define this cluster

◆ Cluster() [3/4]

template<typename T , size_t tDimension, typename TSum , typename TSquareDistance , bool tUseIndices>

Ocean::ClusteringKMeans< T, tDimension, TSum, TSquareDistance, tUseIndices >::Cluster::Cluster	(	const ClusteringKMeans< T, tDimension, TSum, TSquareDistance, tUseIndices > &	owner,
		const Observation &	mean,
		const DataIndices &	dataIndices
	)

inlineprotected

Creates a new cluster object by a given mean value and several indices of observations that belong to this cluster.

Parameters

owner	The owner of this cluster object
mean	The mean observation value that will define this cluster
dataIndices	The data-indices of the observations that belong to this cluster

◆ Cluster() [4/4]

template<typename T , size_t tDimension, typename TSum , typename TSquareDistance , bool tUseIndices>

Ocean::ClusteringKMeans< T, tDimension, TSum, TSquareDistance, tUseIndices >::Cluster::Cluster	(	const ClusteringKMeans< T, tDimension, TSum, TSquareDistance, tUseIndices > &	owner,
		const Observation &	mean,
		DataIndices &&	dataIndices
	)

inlineprotected

Creates a new cluster object by a given mean value and several indices of observations that belong to this cluster.

Parameters

owner	The owner of this cluster object
mean	The mean observation value that will define this cluster
dataIndices	The data-indices of the observations that belong to this cluster; beware: the indices will be moved to this cluster object

Member Function Documentation

◆ averageSqrDistance()

template<typename T , size_t tDimension, typename TSum , typename TSquareDistance , bool tUseIndices>

TSquareDistance Ocean::ClusteringKMeans< T, tDimension, TSum, TSquareDistance, tUseIndices >::Cluster::averageSqrDistance ( ) const

Calculates the average square distance between the mean observation value of this cluster and all observations which belong to this cluster.

Returns: Average square distance

◆ dataIndices() [1/2]

template<typename T , size_t tDimension, typename TSum , typename TSquareDistance , bool tUseIndices>

ClusteringKMeans< T, tDimension, TSum, TSquareDistance, tUseIndices >::DataIndices & Ocean::ClusteringKMeans< T, tDimension, TSum, TSquareDistance, tUseIndices >::Cluster::dataIndices ( )

inlineprotected

Returns the data-indices of the observations that belong to this cluster.

Returns: The cluster's observation indices

◆ dataIndices() [2/2]

template<typename T , size_t tDimension, typename TSum , typename TSquareDistance , bool tUseIndices>

const ClusteringKMeans< T, tDimension, TSum, TSquareDistance, tUseIndices >::DataIndices & Ocean::ClusteringKMeans< T, tDimension, TSum, TSquareDistance, tUseIndices >::Cluster::dataIndices ( ) const

inline

Returns the indices of the observations that belong to this cluster.

Returns: The cluster's observation indices

◆ maximalSqrDistance()

template<typename T , size_t tDimension, typename TSum , typename TSquareDistance , bool tUseIndices>

TSquareDistance Ocean::ClusteringKMeans< T, tDimension, TSum, TSquareDistance, tUseIndices >::Cluster::maximalSqrDistance ( DataIndex * observationIndex = nullptr ) const

Calculates the maximal square distance between the mean observation value of this cluster and all observations which belong to this cluster.

Parameters

observationIndex Optional resulting index of the observation with maximal distance to the mean observation value, if defined

Returns: Maximal square distance

◆ mean()

template<typename T , size_t tDimension, typename TSum , typename TSquareDistance , bool tUseIndices>

const ClusteringKMeans< T, tDimension, TSum, TSquareDistance, tUseIndices >::Observation & Ocean::ClusteringKMeans< T, tDimension, TSum, TSquareDistance, tUseIndices >::Cluster::mean ( ) const

inline

Returns the mean observation value of this cluster.

Returns: The cluster's mean observation value

◆ operator<()

template<typename T , size_t tDimension, typename TSum , typename TSquareDistance , bool tUseIndices>

bool Ocean::ClusteringKMeans< T, tDimension, TSum, TSquareDistance, tUseIndices >::Cluster::operator< ( const Cluster & cluster ) const

inline

Returns whether the left cluster has less elements than the right cluster.

Parameters

cluster The right cluster to compare

Returns: True, if so

◆ operator=()

template<typename T , size_t tDimension, typename TSum , typename TSquareDistance , bool tUseIndices>

ClusteringKMeans< T, tDimension, TSum, TSquareDistance, tUseIndices >::Cluster & Ocean::ClusteringKMeans< T, tDimension, TSum, TSquareDistance, tUseIndices >::Cluster::operator= ( Cluster && cluster )

inlinenoexcept

Move operator moving a cluster object to this object.

Parameters

cluster The cluster object to be moved

Returns: Reference to this object

◆ sqrDistance()

template<typename T , size_t tDimension, typename TSum , typename TSquareDistance , bool tUseIndices>

TSquareDistance Ocean::ClusteringKMeans< T, tDimension, TSum, TSquareDistance, tUseIndices >::Cluster::sqrDistance ( const Observation & observation ) const

inline

Returns the square distance between a given observation and this cluster (the mean observation value of this cluster).

Parameters

observation The observation for that the distance is returned

Returns: Resulting square distance

◆ updateMean()

template<typename T , size_t tDimension, typename TSum , typename TSquareDistance , bool tUseIndices>

void Ocean::ClusteringKMeans< T, tDimension, TSum, TSquareDistance, tUseIndices >::Cluster::updateMean ( )

protected

Updates the mean observation value of this cluster by application of the stored indices of all observations that belong to this cluster.

Friends And Related Symbol Documentation

◆ ClusteringKMeans< T, tDimension, TSum, TSquareDistance, tUseIndices >

template<typename T , size_t tDimension, typename TSum = T, typename TSquareDistance = T, bool tUseIndices = true>

friend class ClusteringKMeans< T, tDimension, TSum, TSquareDistance, tUseIndices >

friend

◆ std::allocator< Cluster >

template<typename T , size_t tDimension, typename TSum = T, typename TSquareDistance = T, bool tUseIndices = true>

friend class std::allocator< Cluster >

friend

Field Documentation

◆ dataIndices_

template<typename T , size_t tDimension, typename TSum = T, typename TSquareDistance = T, bool tUseIndices = true>

DataIndices Ocean::ClusteringKMeans< T, tDimension, TSum, TSquareDistance, tUseIndices >::Cluster::dataIndices_

protected

The data indices of all observation that belong to this cluster.

◆ mean_

template<typename T , size_t tDimension, typename TSum = T, typename TSquareDistance = T, bool tUseIndices = true>

Observation Ocean::ClusteringKMeans< T, tDimension, TSum, TSquareDistance, tUseIndices >::Cluster::mean_

protected

The mean observation value of this cluster.

◆ owner_

template<typename T , size_t tDimension, typename TSum = T, typename TSquareDistance = T, bool tUseIndices = true>

const ClusteringKMeans<T, tDimension, TSum, TSquareDistance, tUseIndices>* Ocean::ClusteringKMeans< T, tDimension, TSum, TSquareDistance, tUseIndices >::Cluster::owner_

protected

The owner of this cluster.

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

ClusteringKMeans.h

Public Member Functions

Protected Member Functions

Protected Attributes

Friends

Detailed Description

Constructor & Destructor Documentation

◆ Cluster() [1/4]

◆ Cluster() [2/4]

◆ Cluster() [3/4]

◆ Cluster() [4/4]

Member Function Documentation

◆ averageSqrDistance()

◆ dataIndices() [1/2]

◆ dataIndices() [2/2]

◆ maximalSqrDistance()

◆ mean()

◆ operator<()

◆ operator=()

◆ sqrDistance()

◆ updateMean()

Friends And Related Symbol Documentation

◆ ClusteringKMeans< T, tDimension, TSum, TSquareDistance, tUseIndices >

◆ std::allocator< Cluster >

Field Documentation

◆ dataIndices_

◆ mean_

◆ owner_