de.lmu.ifi.dbs.elki.index.preprocessed.knn

Class AbstractMaterializeKNNPreprocessor.Factory<O>

java.lang.Object

de.lmu.ifi.dbs.elki.index.preprocessed.knn.AbstractMaterializeKNNPreprocessor.Factory<O>

Type Parameters:

O - The object type

All Implemented Interfaces:

IndexFactory<O,KNNIndex<O>>

Direct Known Subclasses:

CachedDoubleDistanceKNNPreprocessor.Factory, KNNJoinMaterializeKNNPreprocessor.Factory, MaterializeKNNPreprocessor.Factory, MetricalIndexApproximationMaterializeKNNPreprocessor.Factory, PartitionApproximationMaterializeKNNPreprocessor.Factory, RandomSampleKNNPreprocessor.Factory, SpacefillingMaterializeKNNPreprocessor.Factory, SpatialApproximationMaterializeKNNPreprocessor.Factory

Enclosing class:

AbstractMaterializeKNNPreprocessor<O>

public abstract static class AbstractMaterializeKNNPreprocessor.Factory<O>
extends Object
implements IndexFactory<O,KNNIndex<O>>

The parameterizable factory.

Author:

Erich Schubert

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	AbstractMaterializeKNNPreprocessor.Factory.Parameterizer<O> Parameterization class.

Field Summary

Fields

Modifier and Type	Field and Description
static OptionID	DISTANCE_FUNCTION_ID Parameter to indicate the distance function to be used to ascertain the nearest neighbors.
protected DistanceFunction<? super O>	distanceFunction Hold the distance function to be used.
protected int	k Holds the value of K_ID.
static OptionID	K_ID Parameter to specify the number of nearest neighbors of an object to be materialized. must be an integer greater than 1.

Constructor Summary

Constructors

Constructor and Description
AbstractMaterializeKNNPreprocessor.Factory(int k, DistanceFunction<? super O> distanceFunction) Index factory.

Method Summary

Methods

Modifier and Type	Method and Description
DistanceFunction<? super O>	getDistanceFunction() Get the distance function.
TypeInformation	getInputTypeRestriction() Get the input type restriction used for negotiating the data query.
abstract AbstractMaterializeKNNPreprocessor<O>	instantiate(Relation<O> relation) Sets the database in the distance function of this index (if existing).

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Field Detail

K_ID

public static final OptionID K_ID

Parameter to specify the number of nearest neighbors of an object to be materialized. must be an integer greater than 1.

Key: -materialize.k

DISTANCE_FUNCTION_ID

public static final OptionID DISTANCE_FUNCTION_ID

Parameter to indicate the distance function to be used to ascertain the nearest neighbors.

Default value: EuclideanDistanceFunction

Key: materialize.distance

k

protected int k

Holds the value of K_ID.

distanceFunction

protected DistanceFunction<? super O> distanceFunction

Hold the distance function to be used.

Constructor Detail

AbstractMaterializeKNNPreprocessor.Factory

public AbstractMaterializeKNNPreprocessor.Factory(int k,
                                          DistanceFunction<? super O> distanceFunction)

Index factory.

Parameters:

k - k parameter

distanceFunction - distance function

Method Detail

instantiate

public abstract AbstractMaterializeKNNPreprocessor<O> instantiate(Relation<O> relation)

Description copied from interface: IndexFactory

Sets the database in the distance function of this index (if existing).

Specified by:

instantiate in interface IndexFactory<O,KNNIndex<O>>

Parameters:

relation - the relation to index

getDistanceFunction

public DistanceFunction<? super O> getDistanceFunction()

Get the distance function.

Returns:

Distance function

getInputTypeRestriction

public TypeInformation getInputTypeRestriction()

Description copied from interface: IndexFactory

Get the input type restriction used for negotiating the data query.

Specified by:

getInputTypeRestriction in interface IndexFactory<O,KNNIndex<O>>

Returns:

Type restriction