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>

Type Parameters:

D - Distance type

V - Vector type

All Implemented Interfaces:

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 OptionID	DELTA_ID OptionID for DELTA_PARAM
private DoubleParameter	DELTA_PARAM Parameter for 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_ID, 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, logger

Constructor Summary

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

Method Summary

protected void	runVarianceAnalysis(Integer id, List<DistanceResultPair<D>> neighbors, Database<V> database) TODO provide correct commentary This method implements the type of variance analysis to be computed for a given point.
List<String>	setParameters(List<String> args) Grabs all specified options from the option handler.
String	shortDescription() Returns a short description of the class.

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

run

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

addOption, addParameterizable, addParameterizable, checkGlobalParameterConstraints, collectOptions, getAttributeSettings, getParameters, rememberParametersExcept, removeOption, removeParameterizable

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

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

checkGlobalParameterConstraints, collectOptions, getParameters

Field Detail

DEFAULT_DELTA

public static final double DEFAULT_DELTA

The default value for delta.

See Also:

Constant Field Values

DELTA_ID

public static final OptionID DELTA_ID

OptionID for DELTA_PARAM

DELTA_PARAM

private final DoubleParameter DELTA_PARAM

Parameter for Delta

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<DistanceResultPair<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 List<String> setParameters(List<String> args)
                           throws ParameterException

Description copied from class: AbstractParameterizable

Grabs all specified options from the option handler. 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 overwriting this method taking advantage from the previously (in superclasses) defined options would be:

 {
   List 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 ProjectedDBSCANPreprocessor<D extends Distance<D>,V extends RealVector<V,?>>

Parameters:

args - parameters to set the attributes accordingly to

Returns:

a list containing the unused parameters

Throws:

ParameterException - in case of wrong parameter-setting

shortDescription

public String shortDescription()

Description copied from class: AbstractParameterizable

Returns a short description of the class.

Specified by:

shortDescription in interface Parameterizable

Overrides:

shortDescription in class AbstractParameterizable

Returns:

Description of the class