de.lmu.ifi.dbs.elki.algorithm.benchmark

Class ValidateApproximativeKNNIndex.Parameterizer<O,D extends Distance<D>>

java.lang.Object

de.lmu.ifi.dbs.elki.utilities.optionhandling.AbstractParameterizer

de.lmu.ifi.dbs.elki.algorithm.AbstractDistanceBasedAlgorithm.Parameterizer<O,D>

de.lmu.ifi.dbs.elki.algorithm.benchmark.ValidateApproximativeKNNIndex.Parameterizer<O,D>

Type Parameters:

O - Object type

D - Distance type

All Implemented Interfaces:

Parameterizer

Enclosing class:

ValidateApproximativeKNNIndex<O,D extends Distance<D>>

public static class ValidateApproximativeKNNIndex.Parameterizer<O,D extends Distance<D>>
extends AbstractDistanceBasedAlgorithm.Parameterizer<O,D>

Parameterization class

Field Summary

Fields

Modifier and Type	Field and Description
static OptionID	FORCE_ID Force linear scanning.
protected boolean	forcelinear Force linear scanning.
protected int	k K parameter
static OptionID	K_ID Parameter for the number of neighbors.
protected Pattern	pattern Filter pattern for query points.
static OptionID	PATTERN_ID Parameter to select query points.
protected DatabaseConnection	queries The alternate query point source.
static OptionID	QUERY_ID Parameter for the query dataset.
protected RandomFactory	random Random generator factory
static OptionID	RANDOM_ID Parameter for the random generator.
protected double	sampling Sampling size.
static OptionID	SAMPLING_ID Parameter for the sampling size.

Fields inherited from class de.lmu.ifi.dbs.elki.algorithm.AbstractDistanceBasedAlgorithm.Parameterizer

distanceFunction

Constructor Summary

Constructors

Constructor and Description
ValidateApproximativeKNNIndex.Parameterizer()

Method Summary

Methods

Modifier and Type	Method and Description
protected ValidateApproximativeKNNIndex<O,D>	makeInstance() Make an instance after successful configuration.
protected void	makeOptions(Parameterization config) Add all options.

Methods inherited from class de.lmu.ifi.dbs.elki.utilities.optionhandling.AbstractParameterizer

configure, make

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 for the number of neighbors.

QUERY_ID

public static final OptionID QUERY_ID

Parameter for the query dataset.

SAMPLING_ID

public static final OptionID SAMPLING_ID

Parameter for the sampling size.

FORCE_ID

public static final OptionID FORCE_ID

Force linear scanning.

RANDOM_ID

public static final OptionID RANDOM_ID

Parameter for the random generator.

PATTERN_ID

public static final OptionID PATTERN_ID

Parameter to select query points.

k

protected int k

K parameter

queries

protected DatabaseConnection queries

The alternate query point source. Optional.

sampling

protected double sampling

Sampling size.

forcelinear

protected boolean forcelinear

Force linear scanning.

random

protected RandomFactory random

Random generator factory

pattern

protected Pattern pattern

Filter pattern for query points.

Constructor Detail

ValidateApproximativeKNNIndex.Parameterizer

public ValidateApproximativeKNNIndex.Parameterizer()

Method Detail

makeOptions

protected void makeOptions(Parameterization config)

Description copied from class: AbstractParameterizer

Add all options. ALWAYS call super.makeOptions(config), unless you have a strong reason to do otherwise!

Overrides:

makeOptions in class AbstractDistanceBasedAlgorithm.Parameterizer<O,D extends Distance<D>>

Parameters:

config - Parameterization to add options to.

makeInstance

protected ValidateApproximativeKNNIndex<O,D> makeInstance()

Description copied from class: AbstractParameterizer

Make an instance after successful configuration.

Specified by:

makeInstance in class AbstractParameterizer

Returns:

instance