de.lmu.ifi.dbs.elki.preprocessing
Class ProjectedDBSCANPreprocessor<D extends Distance<D>,V extends FeatureVector<V,?>>

java.lang.Object
  de.lmu.ifi.dbs.elki.logging.AbstractLoggable
      de.lmu.ifi.dbs.elki.preprocessing.ProjectedDBSCANPreprocessor<D,V>

Type Parameters:

D - Distance type

V - Vector type

All Implemented Interfaces:

Preprocessor<V>

Direct Known Subclasses:

FourCPreprocessor, PreDeConPreprocessor

public abstract class ProjectedDBSCANPreprocessor<D extends Distance<D>,V extends FeatureVector<V,?>>
extends AbstractLoggable
implements Preprocessor<V>

Abstract superclass for preprocessor of algorithms extending the ProjectedDBSCAN algorithm.

Author:

Arthur Zimek

Field Summary

static Class<?>	DEFAULT_DISTANCE_FUNCTION The default range query distance function.
private ObjectParameter<DistanceFunction<V,D>>	DISTANCE_FUNCTION_PARAM Parameter distance function
private D	epsilon Contains the value of parameter epsilon;
DistanceParameter<D>	EPSILON_PARAM Parameter to specify the maximum radius of the neighborhood to be considered, must be suitable to LocallyWeightedDistanceFunction.
private int	minpts Holds the value of parameter minpts.
private IntParameter	MINPTS_PARAM Parameter to specify the threshold for minimum number of points in the epsilon-neighborhood of a point, must be an integer greater than 0.
protected DistanceFunction<V,D>	rangeQueryDistanceFunction The distance function for the variance analysis.

Fields inherited from class de.lmu.ifi.dbs.elki.logging.AbstractLoggable

debug, logger

Constructor Summary

protected

ProjectedDBSCANPreprocessor(Parameterization config) Provides a new Preprocessor that computes the correlation dimension of objects of a certain database.

Method Summary

void	run(Database<V> database, boolean verbose, boolean time) This method executes the particular preprocessing step of this Preprocessor for the objects of the specified database.
protected abstract void	runVarianceAnalysis(Integer id, List<DistanceResultPair<D>> neighbors, Database<V> database) This method implements the type of variance analysis to be computed for a given point.

Methods inherited from class de.lmu.ifi.dbs.elki.logging.AbstractLoggable

debugFine, debugFiner, debugFinest, exception, progress, verbose, warning

Methods inherited from class java.lang.Object

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

Field Detail

EPSILON_PARAM

public final DistanceParameter<D extends Distance<D>> EPSILON_PARAM

Parameter to specify the maximum radius of the neighborhood to be considered, must be suitable to LocallyWeightedDistanceFunction.

Key: -epsilon

MINPTS_PARAM

private final IntParameter MINPTS_PARAM

Parameter to specify the threshold for minimum number of points in the epsilon-neighborhood of a point, must be an integer greater than 0.

Key: -projdbscan.minpts

DEFAULT_DISTANCE_FUNCTION

public static final Class<?> DEFAULT_DISTANCE_FUNCTION

The default range query distance function.

DISTANCE_FUNCTION_PARAM

private final ObjectParameter<DistanceFunction<V extends FeatureVector<V,?>,D extends Distance<D>>> DISTANCE_FUNCTION_PARAM

Parameter distance function

epsilon

private D extends Distance<D> epsilon

Contains the value of parameter epsilon;

rangeQueryDistanceFunction

protected DistanceFunction<V extends FeatureVector<V,?>,D extends Distance<D>> rangeQueryDistanceFunction

The distance function for the variance analysis.

minpts

private int minpts

Holds the value of parameter minpts.

Constructor Detail

ProjectedDBSCANPreprocessor

protected ProjectedDBSCANPreprocessor(Parameterization config)

Provides a new Preprocessor that computes the correlation dimension of objects of a certain database.

Method Detail

run

public void run(Database<V> database,
                boolean verbose,
                boolean time)

Description copied from interface: Preprocessor

This method executes the particular preprocessing step of this Preprocessor for the objects of the specified database.

Specified by:

run in interface Preprocessor<V extends FeatureVector<V,?>>

Parameters:

database - the database for which the preprocessing is performed

verbose - flag to allow verbose messages while performing the algorithm

time - flag to request output of performance time

runVarianceAnalysis

protected abstract void runVarianceAnalysis(Integer id,
                                            List<DistanceResultPair<D>> neighbors,
                                            Database<V> database)

This method implements the type of variance analysis to be computed for a given point.

Example1: for 4C, this method should implement a PCA for the given point. Example2: for PreDeCon, this method should implement a simple axis-parallel variance analysis.

Parameters:

id - the given point

neighbors - the neighbors as query results of the given point

database - the database for which the preprocessing is performed