mlpack::neighbor::QDAFN< MatType > Class Template Reference

Public Member Functions
	QDAFN (const size_t l, const size_t m)
	Construct the QDAFN object but do not train it. More...
	QDAFN (const MatType &referenceSet, const size_t l, const size_t m)
	Construct the QDAFN object with the given reference set (this is the set that will be searched). More...
void	Train (const MatType &referenceSet, const size_t l=0, const size_t m=0)
	Train the QDAFN model on the given reference set, optionally setting new parameters for the number of projections/tables (l) and the number of elements stored for each projection/table (m). More...
void	Search (const MatType &querySet, const size_t k, arma::Mat< size_t > &neighbors, arma::mat &distances)
	Search for the k furthest neighbors of the given query set. More...
template<typename Archive >
void	serialize (Archive &ar, const uint32_t)
	Serialize the model.
size_t	NumProjections () const
	Get the number of projections.
const MatType &	CandidateSet (const size_t t) const
	Get the candidate set for the given projection table.
MatType &	CandidateSet (const size_t t)
	Modify the candidate set for the given projection table. Careful!

Constructor & Destructor Documentation

QDAFN() [1/2]

template<typename MatType >

mlpack::neighbor::QDAFN< MatType >::QDAFN	(	const size_t	l,
		const size_t	m
	)

Construct the QDAFN object but do not train it.

Be sure to call Train() before calling Search().

Parameters

l	Number of projections.
m	Number of elements to store for each projection.

QDAFN() [2/2]

template<typename MatType >

mlpack::neighbor::QDAFN< MatType >::QDAFN	(	const MatType &	referenceSet,
		const size_t	l,
		const size_t	m
	)

Construct the QDAFN object with the given reference set (this is the set that will be searched).

Parameters

referenceSet	Set of reference data.
l	Number of projections.
m	Number of elements to store for each projection.

Member Function Documentation

Search()

template<typename MatType >

void mlpack::neighbor::QDAFN< MatType >::Search	(	const MatType &	querySet,
		const size_t	k,
		arma::Mat< size_t > &	neighbors,
		arma::mat &	distances
	)

Search for the k furthest neighbors of the given query set.

(The query set can contain just one point, that is okay.) The results will be stored in the given neighbors and distances matrices, in the same format as the mlpack NeighborSearch and LSHSearch classes.

Train()

template<typename MatType >

void mlpack::neighbor::QDAFN< MatType >::Train	(	const MatType &	referenceSet,
		const size_t	l = 0,
		const size_t	m = 0
	)

Train the QDAFN model on the given reference set, optionally setting new parameters for the number of projections/tables (l) and the number of elements stored for each projection/table (m).

Parameters

referenceSet	Reference set to train on.
l	Number of projections.
m	Number of elements to store for each projection.

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

• src/mlpack/methods/approx_kfn/qdafn.hpp
• src/mlpack/methods/approx_kfn/qdafn_impl.hpp