de.lmu.ifi.dbs.elki.preprocessing
Class DiSHPreprocessor<V extends RealVector<V,N>,N extends Number>

java.lang.Object
  de.lmu.ifi.dbs.elki.logging.AbstractLoggable
      de.lmu.ifi.dbs.elki.utilities.optionhandling.AbstractParameterizable
          de.lmu.ifi.dbs.elki.preprocessing.DiSHPreprocessor<V,N>

All Implemented Interfaces:

Loggable, PreferenceVectorPreprocessor<V>, Preprocessor<V>, Parameterizable

public class DiSHPreprocessor<V extends RealVector<V,N>,N extends Number>
extends AbstractParameterizable
implements PreferenceVectorPreprocessor<V>

Preprocessor for DiSH preference vector assignment to objects of a certain database.

Author:

Elke Achtert

Nested Class Summary

static class

DiSHPreprocessor.Strategy Available strategies for determination of the preference vecrtor.

Field Summary

private static String	CONDITION Description for the determination of the preference vector.
static DoubleDistance	DEFAULT_EPSILON The default value for epsilon.
static DiSHPreprocessor.Strategy	DEFAULT_STRATEGY Default strategy.
private DoubleDistance[]	epsilon The epsilon value for each dimension;
static String	EPSILON_D Description for parameter epsilon.
static String	EPSILON_P Option string for parameter epsilon.
private int	minpts Threshold for minimum number of points in the neighborhood.
static String	MINPTS_D Description for parameter minimum points.
static String	MINPTS_P Parameter minimum points.
private DiSHPreprocessor.Strategy	strategy The strategy to determine the preference vector.
static String	STRATEGY_D Description for parameter strategy.
static String	STRATEGY_P Parameter strategy.

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

DiSHPreprocessor()
Provides a new AdvancedHiSCPreprocessor that computes the preference vector of objects of a certain database.

Method Summary

String	description() Returns a description of the class and the required parameters.
private BitSet	determinePreferenceVector(Database<V> database, Set<Integer>[] neighborIDs, StringBuffer msg) Determines the preference vector according to the specified neighbor ids.
private BitSet	determinePreferenceVectorByApriori(Database<V> database, Set<Integer>[] neighborIDs, StringBuffer msg) Determines the preference vector with the apriori strategy.
private BitSet	determinePreferenceVectorByMaxIntersection(Set<Integer>[] neighborIDs, StringBuffer msg) Determines the preference vector with the max intersection strategy.
DoubleDistance[]	getEpsilon() Returns the value of the epsilon parameter.
int	getMinpts() Returns minpts.
private DimensionSelectingDistanceFunction<N,V>[]	initDistanceFunctions(Database<V> database, int dimensionality, boolean verbose, boolean time) Initializes the dimension selecting distancefunctions to determine the preference vectors.
private int	max(Map<Integer,Set<Integer>> candidates) Returns the set with the maximum size contained in the specified map.
private int	maxIntersection(Map<Integer,Set<Integer>> candidates, Set<Integer> set, Set<Integer> result) Returns the index of the set having the maximum intersection set with the specified set contained in the specified map.
void	run(Database<V> database, boolean verbose, boolean time) This method executes the actual preprocessing step of this Preprocessor for the objects of the specified database.
String[]	setParameters(String[] args) Sets the attributes of the class accordingly to the given parameters.

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

addOption, checkGlobalParameterConstraints, deleteOption, description, description, getAttributeSettings, 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, getAttributeSettings, getParameters, getPossibleOptions, inlineDescription

Field Detail

DEFAULT_EPSILON

public static final DoubleDistance DEFAULT_EPSILON

The default value for epsilon.

EPSILON_P

public static final String EPSILON_P

Option string for parameter epsilon.

See Also:

Constant Field Values

EPSILON_D

public static String EPSILON_D

Description for parameter epsilon.

MINPTS_P

public static final String MINPTS_P

Parameter minimum points.

See Also:

Constant Field Values

CONDITION

private static final String CONDITION

Description for the determination of the preference vector.

See Also:

Constant Field Values

MINPTS_D

public static final String MINPTS_D

Description for parameter minimum points.

See Also:

Constant Field Values

STRATEGY_P

public static final String STRATEGY_P

Parameter strategy.

See Also:

Constant Field Values

DEFAULT_STRATEGY

public static DiSHPreprocessor.Strategy DEFAULT_STRATEGY

Default strategy.

STRATEGY_D

public static final String STRATEGY_D

Description for parameter strategy.

epsilon

private DoubleDistance[] epsilon

The epsilon value for each dimension;

minpts

private int minpts

Threshold for minimum number of points in the neighborhood.

strategy

private DiSHPreprocessor.Strategy strategy

The strategy to determine the preference vector.

Constructor Detail

DiSHPreprocessor

public DiSHPreprocessor()

Provides a new AdvancedHiSCPreprocessor that computes the preference vector 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 actual preprocessing step of this Preprocessor for the objects of the specified database.

Specified by:

run in interface Preprocessor<V extends RealVector<V,N>>

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

See Also:

Preprocessor.run(de.lmu.ifi.dbs.elki.database.Database,boolean,boolean)

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()

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 AbstractParameterizable

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[])

determinePreferenceVector

private BitSet determinePreferenceVector(Database<V> database,
                                         Set<Integer>[] neighborIDs,
                                         StringBuffer msg)
                                  throws ParameterException,
                                         UnableToComplyException

Determines the preference vector according to the specified neighbor ids.

Parameters:

database - the database storing the objects

neighborIDs - the list of ids of the neighbors in each dimension

msg - a string buffer for debug messages

Returns:

the preference vector

Throws:

ParameterException

UnableToComplyException

determinePreferenceVectorByApriori

private BitSet determinePreferenceVectorByApriori(Database<V> database,
                                                  Set<Integer>[] neighborIDs,
                                                  StringBuffer msg)
                                           throws ParameterException,
                                                  UnableToComplyException

Determines the preference vector with the apriori strategy.

Parameters:

database - the database storing the objects

neighborIDs - the list of ids of the neighbors in each dimension

msg - a string buffer for debug messages

Returns:

the preference vector

Throws:

ParameterException

UnableToComplyException

determinePreferenceVectorByMaxIntersection

private BitSet determinePreferenceVectorByMaxIntersection(Set<Integer>[] neighborIDs,
                                                          StringBuffer msg)

Determines the preference vector with the max intersection strategy.

Parameters:

neighborIDs - the list of ids of the neighbors in each dimension

msg - a string buffer for debug messages

Returns:

the preference vector

max

private int max(Map<Integer,Set<Integer>> candidates)

Returns the set with the maximum size contained in the specified map.

Parameters:

candidates - the map containing the sets

Returns:

the set with the maximum size

maxIntersection

private int maxIntersection(Map<Integer,Set<Integer>> candidates,
                            Set<Integer> set,
                            Set<Integer> result)

Returns the index of the set having the maximum intersection set with the specified set contained in the specified map.

Parameters:

candidates - the map containing the sets

set - the set to intersect with

result - the set to put the result in

Returns:

the set with the maximum size

initDistanceFunctions

private DimensionSelectingDistanceFunction<N,V>[] initDistanceFunctions(Database<V> database,
                                                                        int dimensionality,
                                                                        boolean verbose,
                                                                        boolean time)
                                                                                                        throws ParameterException

Initializes the dimension selecting distancefunctions to determine the preference vectors.

Parameters:

database - the database storing the objects

dimensionality - the dimensionality of the objects

verbose - flag to allow verbose messages while performing the algorithm

time - flag to request output of performance time

Returns:

the dimension selecting distancefunctions to determine the preference vectors

Throws:

ParameterException

getEpsilon

public DoubleDistance[] getEpsilon()

Returns the value of the epsilon parameter.

Returns:

the value of the epsilon parameter

getMinpts

public int getMinpts()

Returns minpts.

Returns:

minpts