Package elki.application.statistics

Class EstimateIntrinsicDimensionality<O>

java.lang.Object

elki.application.AbstractApplication

elki.application.AbstractDistanceBasedApplication<O>

elki.application.statistics.EstimateIntrinsicDimensionality<O>

Type Parameters:

O - Data type

public class EstimateIntrinsicDimensionality<O>
extends AbstractDistanceBasedApplication<O>

Estimate global average intrinsic dimensionality of a data set.

The output will be logged at the statistics level.

Since:

0.7.0

Author:

Erich Schubert

Field Summary

Fields

Modifier and Type	Field	Description
protected IntrinsicDimensionalityEstimator<? super O>	estimator	Estimation method.
protected double	krate	Number of neighbors to use.
private static Logging	LOG	Class logger.
protected double	samples	Number of samples to draw.

Fields inherited from class elki.application.AbstractDistanceBasedApplication

distance, inputstep

Fields inherited from class elki.application.AbstractApplication

REFERENCE, VERSION

Constructor Summary

Constructors

Constructor	Description
EstimateIntrinsicDimensionality(InputStep inputstep, Distance<? super O> distance, IntrinsicDimensionalityEstimator<? super O> estimator, double krate, double samples)	Constructor.

Method Summary

Modifier and Type	Method	Description
void	run()	Runs the application.

Methods inherited from class elki.application.AbstractApplication

printErrorMessage, runCLIApplication, usage

Methods inherited from class java.lang.Object

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

Field Detail

LOG

private static final Logging LOG

Class logger.

krate

protected double krate

Number of neighbors to use.

samples

protected double samples

Number of samples to draw.

estimator

protected IntrinsicDimensionalityEstimator<? super O> estimator

Estimation method.

Constructor Detail

EstimateIntrinsicDimensionality

public EstimateIntrinsicDimensionality(InputStep inputstep,
                                       Distance<? super O> distance,
                                       IntrinsicDimensionalityEstimator<? super O> estimator,
                                       double krate,
                                       double samples)

Constructor.

Parameters:

inputstep - Data input step

distance - Distance function

estimator - Estimator

krate - kNN rate

samples - Sample size

Method Detail

run

public void run()

Description copied from class: AbstractApplication

Runs the application.

Specified by:

run in class AbstractApplication