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

Class RandomSampleKNNPreprocessor.Factory<O,D extends Distance<D>>

java.lang.Object

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

de.lmu.ifi.dbs.elki.index.preprocessed.knn.RandomSampleKNNPreprocessor.Factory<O,D>

Type Parameters:

O - The object type

D - The distance type

All Implemented Interfaces:

IndexFactory<O,KNNIndex<O>>, InspectionUtilFrequentlyScanned, Parameterizable

Enclosing class:

RandomSampleKNNPreprocessor<O,D extends Distance<D>>

public static class RandomSampleKNNPreprocessor.Factory<O,D extends Distance<D>>
extends AbstractMaterializeKNNPreprocessor.Factory<O,D,KNNResult<D>>

The parameterizable factory.

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	RandomSampleKNNPreprocessor.Factory.Parameterizer<O,D extends Distance<D>> Parameterization class

Field Summary

Fields

Modifier and Type	Field and Description
private RandomFactory	rnd Random generator
private double	share Relative share of objects to get

Fields inherited from class de.lmu.ifi.dbs.elki.index.preprocessed.knn.AbstractMaterializeKNNPreprocessor.Factory

DISTANCE_FUNCTION_ID, distanceFunction, k, K_ID

Constructor Summary

Constructors

Constructor and Description
RandomSampleKNNPreprocessor.Factory(int k, DistanceFunction<? super O,D> distanceFunction, double share, RandomFactory rnd) Constructor.

Method Summary

Methods

Modifier and Type	Method and Description
RandomSampleKNNPreprocessor<O,D>	instantiate(Relation<O> relation) Sets the database in the distance function of this index (if existing).

Methods inherited from class de.lmu.ifi.dbs.elki.index.preprocessed.knn.AbstractMaterializeKNNPreprocessor.Factory

getDistanceFactory, getDistanceFunction, getInputTypeRestriction

Methods inherited from class java.lang.Object

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

Field Detail

share

private final double share

Relative share of objects to get

rnd

private final RandomFactory rnd

Random generator

Constructor Detail

RandomSampleKNNPreprocessor.Factory

public RandomSampleKNNPreprocessor.Factory(int k,
                                   DistanceFunction<? super O,D> distanceFunction,
                                   double share,
                                   RandomFactory rnd)

Constructor.

Parameters:

k - K

distanceFunction - distance function

share - Sample size (relative)

rnd - Random generator

Method Detail

instantiate

public RandomSampleKNNPreprocessor<O,D> 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>>

Specified by:

instantiate in class AbstractMaterializeKNNPreprocessor.Factory<O,D extends Distance<D>,KNNResult<D extends Distance<D>>>

Parameters:

relation - the relation to index