de.lmu.ifi.dbs.elki.algorithm.clustering.subspace
Class ProjectedClustering<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.algorithm.AbstractAlgorithm<V>
              de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.ProjectedClustering<V>

Type Parameters:

V - the type of Realvector handled by this Algorithm

All Implemented Interfaces:

Algorithm<V>, Clustering<V>, Loggable, Parameterizable

Direct Known Subclasses:

ORCLUS, PROCLUS

public abstract class ProjectedClustering<V extends RealVector<V,?>>
extends AbstractAlgorithm<V>
implements Clustering<V>

Abstract superclass for PROCLUS and ORCLUS.

Author:

Elke Achtert

Field Summary

private EuklideanDistanceFunction<V>	distanceFunction The euklidean distance function.
private int	k Number of clusters.
private int	k_i Multiplier for initial number of seeds.
static OptionID	K_I_ID OptionID for K_I_PARAM
private IntParameter	K_I_PARAM Parameter to specify the multiplier for the initial number of seeds, must be an integer greater than 0.
static OptionID	K_ID OptionID for K_PARAM
private IntParameter	K_PARAM Parameter to specify the number of clusters to find, must be an integer greater than 0.
private int	l Dimensionality of the clusters.
static OptionID	L_ID OptionID for L_PARAM
private IntParameter	L_PARAM Parameter to specify the dimensionality of the clusters to find, must be an integer greater than 0.
private Clusters<V>	result The result.

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

ProjectedClustering()
Sets the parameter k and l the optionhandler additionally to the parameters provided by super-classes.

Method Summary

protected EuklideanDistanceFunction<V>	getDistanceFunction() Returns the distance function.
protected int	getK_i() Returns the value of parameter k_i.
protected int	getK() Returns the value of parameter k.
protected int	getL() Returns the value of parameter l.
Clusters<V>	getResult() Returns the result of the algorithm.
String[]	setParameters(String[] args) Grabs all specified options from the option handler and sets the values for the flags AbstractAlgorithm.VERBOSE_FLAG and AbstractAlgorithm.TIME_FLAG.
protected void	setResult(Clusters<V> result) Sets the result of this algorithm.

Methods inherited from class de.lmu.ifi.dbs.elki.algorithm.AbstractAlgorithm

description, isTime, isVerbose, run, runInTime, setTime, setVerbose

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.algorithm.Algorithm

getDescription, run, setTime, setVerbose

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

checkGlobalParameterConstraints, description, getAttributeSettings, getParameters, getPossibleOptions, inlineDescription

Field Detail

K_ID

public static final OptionID K_ID

OptionID for K_PARAM

K_I_ID

public static final OptionID K_I_ID

OptionID for K_I_PARAM

L_ID

public static final OptionID L_ID

OptionID for L_PARAM

K_PARAM

private final IntParameter K_PARAM

Parameter to specify the number of clusters to find, must be an integer greater than 0.

Key: -projectedclustering.k

K_I_PARAM

private final IntParameter K_I_PARAM

Parameter to specify the multiplier for the initial number of seeds, must be an integer greater than 0.

Default value: 30

Key: -projectedclustering.k_i

L_PARAM

private final IntParameter L_PARAM

Parameter to specify the dimensionality of the clusters to find, must be an integer greater than 0.

Key: -projectedclustering.l

k

private int k

Number of clusters.

k_i

private int k_i

Multiplier for initial number of seeds.

l

private int l

Dimensionality of the clusters.

distanceFunction

private EuklideanDistanceFunction<V extends RealVector<V,?>> distanceFunction

The euklidean distance function.

result

private Clusters<V extends RealVector<V,?>> result

The result.

Constructor Detail

ProjectedClustering

public ProjectedClustering()

Sets the parameter k and l the optionhandler additionally to the parameters provided by super-classes.

Method Detail

setParameters

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

Description copied from class: AbstractAlgorithm

Grabs all specified options from the option handler and sets the values for the flags AbstractAlgorithm.VERBOSE_FLAG and AbstractAlgorithm.TIME_FLAG. Any extending class should call this method first and return the returned array without further changes, but after setting further required parameters. An example for overwritting this method taking advantage from the previously (in superclasses) defined options would be:

 {
   String[] remainingParameters = super.setParameters(args);
   // set parameters for your class
   // for example like this:
   if(isSet(MY_PARAM_VALUE_PARAM))
   {
      myParamValue = getParameterValue(MY_PARAM_VALUE_PARAM);
   }
   .
   .
   .
   return remainingParameters;
   // or in case of attributes requesting parameters themselves
   // return parameterizableAttribbute.setParameters(remainingParameters);
 }
 

Specified by:

setParameters in interface Parameterizable

Overrides:

setParameters in class AbstractAlgorithm<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[])

getResult

public Clusters<V> getResult()

Description copied from interface: Algorithm

Returns the result of the algorithm.

Specified by:

getResult in interface Algorithm<V extends RealVector<V,?>>

Specified by:

getResult in interface Clustering<V extends RealVector<V,?>>

Returns:

the result of the algorithm

See Also:

Clustering.getResult()

getDistanceFunction

protected EuklideanDistanceFunction<V> getDistanceFunction()

Returns the distance function.

Returns:

the distance function

getK

protected int getK()

Returns the value of parameter k.

Returns:

the number of clusters to be found

getK_i

protected int getK_i()

Returns the value of parameter k_i.

Returns:

the initial number of clusters

getL

protected int getL()

Returns the value of parameter l.

Returns:

the average dimesnionality of the clusters to be found

setResult

protected void setResult(Clusters<V> result)

Sets the result of this algorithm.

Parameters:

result - the result to be set