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

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

All Implemented Interfaces:

Loggable, Preprocessor<V>, Parameterizable

public class PreDeConPreprocessor<D extends Distance<D>,V extends RealVector<V,?>>
extends ProjectedDBSCANPreprocessor<D,V>

Preprocessor for PreDeCon local dimensionality and locally weighted matrix assignment to objects of a certain database.

Author:

Peer Kröger

Field Summary

static double	DEFAULT_DELTA The default value for delta.
protected double	delta The threshold for small eigenvalues.
static String	DELTA_D Description for parameter delta.
static String	DELTA_P Option string for parameter delta.
private int	kappa The kappa value for generating the variance vector.

Fields inherited from class de.lmu.ifi.dbs.elki.preprocessing.ProjectedDBSCANPreprocessor

DEFAULT_DISTANCE_FUNCTION, DISTANCE_FUNCTION_D, DISTANCE_FUNCTION_P, EPSILON_PARAM, rangeQueryDistanceFunction

Fields inherited from class de.lmu.ifi.dbs.elki.utilities.optionhandling.AbstractParameterizable

optionHandler

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

debug

Constructor Summary

PreDeConPreprocessor()
Provides a new Preprocessor that computes the local dimensionality and locally weighted matrix of objects of a certain database.

Method Summary

String	description() Returns a description of the class and the required parameters.
protected void	runVarianceAnalysis(Integer id, List<QueryResult<D>> neighbors, Database<V> database) TODO provide correct commentary This method implements the type of variance analysis to be computed for a given point.
String[]	setParameters(String[] args) Sets the attributes of the class accordingly to the given parameters.

Methods inherited from class de.lmu.ifi.dbs.elki.preprocessing.ProjectedDBSCANPreprocessor

getAttributeSettings, run

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

addOption, checkGlobalParameterConstraints, deleteOption, description, description, getParameters, getParameterValue, getPossibleOptions, inlineDescription, isSet, setParameters

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

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

Methods inherited from class java.lang.Object

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

Methods inherited from interface de.lmu.ifi.dbs.elki.utilities.optionhandling.Parameterizable

checkGlobalParameterConstraints, getParameters, getPossibleOptions, inlineDescription

Field Detail

DEFAULT_DELTA

public static final double DEFAULT_DELTA

The default value for delta.

See Also:

Constant Field Values

DELTA_P

public static final String DELTA_P

Option string for parameter delta.

See Also:

Constant Field Values

DELTA_D

public static final String DELTA_D

Description for parameter delta.

See Also:

Constant Field Values

delta

protected double delta

The threshold for small eigenvalues.

kappa

private final int kappa

The kappa value for generating the variance vector.

See Also:

Constant Field Values

Constructor Detail

PreDeConPreprocessor

public PreDeConPreprocessor()

Provides a new Preprocessor that computes the local dimensionality and locally weighted matrix of objects of a certain database.

Method Detail

runVarianceAnalysis

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

TODO provide correct commentary 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.

Specified by:

runVarianceAnalysis in class ProjectedDBSCANPreprocessor<D extends Distance<D>,V extends RealVector<V,?>>

Parameters:

id - the given point

neighbors - the neighbors as query results of the given point

database - the database for which the preprocessing is performed

setParameters

public String[] setParameters(String[] args)
                       throws ParameterException

Description copied from interface: Parameterizable

Sets the attributes of the class accordingly to the given parameters. Returns a new String array containing those entries of the given array that are neither expected nor used by this Parameterizable.

Specified by:

setParameters in interface Parameterizable

Overrides:

setParameters in class ProjectedDBSCANPreprocessor<D extends Distance<D>,V extends RealVector<V,?>>

Parameters:

args - parameters to set the attributes accordingly to

Returns:

String[] an array containing the unused parameters

Throws:

ParameterException - in case of wrong parameter-setting

See Also:

Parameterizable.setParameters(String[])

description

public String description()

Description copied from interface: Parameterizable

Returns a description of the class and the required parameters.

This description should be suitable for a usage description as for a standalone application.

Specified by:

description in interface Parameterizable

Overrides:

description in class AbstractParameterizable

Returns:

String a description of the class and the required parameters

See Also:

Parameterizable.description()