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java.lang.Object de.lmu.ifi.dbs.elki.logging.AbstractLoggable de.lmu.ifi.dbs.elki.utilities.optionhandling.AbstractParameterizable de.lmu.ifi.dbs.elki.distance.AbstractMeasurementFunction<O,D> de.lmu.ifi.dbs.elki.distance.distancefunction.AbstractDistanceFunction<O,D> de.lmu.ifi.dbs.elki.distance.distancefunction.AbstractPreprocessorBasedDistanceFunction<O,P,D> de.lmu.ifi.dbs.elki.distance.distancefunction.AbstractCorrelationDistanceFunction<O,P,PreferenceVectorBasedCorrelationDistance> de.lmu.ifi.dbs.elki.distance.distancefunction.PreferenceVectorBasedCorrelationDistanceFunction<O,P>
public abstract class PreferenceVectorBasedCorrelationDistanceFunction<O extends RealVector<O,?>,P extends Preprocessor<O>>
XXX unify CorrelationDistanceFunction and VarianceDistanceFunction
Field Summary | |
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static AssociationID |
ASSOCIATION_ID
The Assocoiation ID for the association to be set by the preprocessor. |
static double |
DEFAULT_EPSILON
The default value for epsilon. |
private double |
epsilon
Holds the value of epsilon parameter. |
static String |
EPSILON_D
Description for parameter epsilon. |
static String |
EPSILON_P
Option string for parameter epsilon. |
static Class<PreferenceVectorPreprocessor> |
PREPROCESSOR_SUPER_CLASS
The super class for the preprocessor. |
Fields inherited from class de.lmu.ifi.dbs.elki.distance.distancefunction.AbstractCorrelationDistanceFunction |
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SEPARATOR |
Fields inherited from class de.lmu.ifi.dbs.elki.distance.AbstractMeasurementFunction |
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INFINITY_PATTERN |
Fields inherited from class de.lmu.ifi.dbs.elki.utilities.optionhandling.AbstractParameterizable |
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optionHandler |
Fields inherited from class de.lmu.ifi.dbs.elki.logging.AbstractLoggable |
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debug |
Constructor Summary | |
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PreferenceVectorBasedCorrelationDistanceFunction()
Provides a preference vector based CorrelationDistanceFunction. |
Method Summary | |
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protected PreferenceVectorBasedCorrelationDistance |
correlationDistance(O v1,
O v2)
Computes the correlation distance between the two specified vectors. |
abstract PreferenceVectorBasedCorrelationDistance |
correlationDistance(O v1,
O v2,
BitSet pv1,
BitSet pv2)
Computes the correlation distance between the two specified vectors according to the specified preference vectors. |
(package private) AssociationID |
getAssociationID()
Returns the assocoiation ID for the association to be set by the preprocessor. |
double |
getEpsilon()
Returns epsilon. |
(package private) Class<PreferenceVectorPreprocessor> |
getPreprocessorSuperClassName()
Returns the super class for the preprocessor. |
PreferenceVectorBasedCorrelationDistance |
infiniteDistance()
Provides an infinite distance. |
PreferenceVectorBasedCorrelationDistance |
nullDistance()
Provides a null distance. |
String[] |
setParameters(String[] args)
Sets the values for the parameters delta and preprocessor if specified. |
PreferenceVectorBasedCorrelationDistance |
undefinedDistance()
Provides an undefined distance. |
PreferenceVectorBasedCorrelationDistance |
valueOf(String pattern)
Provides a distance suitable to this DistanceFunction based on the given pattern. |
double |
weightedDistance(Integer id1,
Integer id2,
BitSet weightVector)
Computes the weighted distance between the two specified vectors according to the given preference vector. |
double |
weightedDistance(O dv1,
O dv2,
BitSet weightVector)
Computes the weighted distance between the two specified vectors according to the given preference vector. |
double |
weightedPrefereneceVectorDistance(Integer id1,
Integer id2)
Computes the weighted distance between the two specified data vectors according to their preference vectors. |
double |
weightedPrefereneceVectorDistance(O rv1,
O rv2)
Computes the weighted distance between the two specified data vectors according to their preference vectors. |
Methods inherited from class de.lmu.ifi.dbs.elki.distance.distancefunction.AbstractCorrelationDistanceFunction |
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description, distance, getDefaultPreprocessorClassName, getPreprocessorClassDescription |
Methods inherited from class de.lmu.ifi.dbs.elki.distance.distancefunction.AbstractPreprocessorBasedDistanceFunction |
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getAttributeSettings, getPreprocessor, setDatabase |
Methods inherited from class de.lmu.ifi.dbs.elki.distance.distancefunction.AbstractDistanceFunction |
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distance, distance, isInfiniteDistance, isNullDistance, isUndefinedDistance |
Methods inherited from class de.lmu.ifi.dbs.elki.distance.AbstractMeasurementFunction |
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getDatabase, matches, requiredInputPattern, setRequiredInputPattern |
Methods inherited from class de.lmu.ifi.dbs.elki.utilities.optionhandling.AbstractParameterizable |
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addOption, checkGlobalParameterConstraints, deleteOption, description, description, getParameters, getParameterValue, getPossibleOptions, inlineDescription, isSet, setParameters |
Methods inherited from class de.lmu.ifi.dbs.elki.logging.AbstractLoggable |
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debugFine, debugFiner, debugFinest, exception, message, progress, progress, progress, verbose, verbose, warning |
Methods inherited from class java.lang.Object |
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clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
Methods inherited from interface de.lmu.ifi.dbs.elki.distance.MeasurementFunction |
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requiredInputPattern |
Methods inherited from interface de.lmu.ifi.dbs.elki.utilities.optionhandling.Parameterizable |
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checkGlobalParameterConstraints, getParameters, getPossibleOptions, inlineDescription |
Field Detail |
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public static final AssociationID ASSOCIATION_ID
public static final Class<PreferenceVectorPreprocessor> PREPROCESSOR_SUPER_CLASS
public static final double DEFAULT_EPSILON
public static final String EPSILON_P
public static String EPSILON_D
private double epsilon
Constructor Detail |
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public PreferenceVectorBasedCorrelationDistanceFunction()
Method Detail |
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public PreferenceVectorBasedCorrelationDistance valueOf(String pattern) throws IllegalArgumentException
pattern
- A pattern defining a distance suitable to this
DistanceFunction
IllegalArgumentException
- if the given pattern is not compatible with the requirements
of this DistanceFunctionpublic PreferenceVectorBasedCorrelationDistance infiniteDistance()
public PreferenceVectorBasedCorrelationDistance nullDistance()
public PreferenceVectorBasedCorrelationDistance undefinedDistance()
protected PreferenceVectorBasedCorrelationDistance correlationDistance(O v1, O v2)
AbstractCorrelationDistanceFunction
correlationDistance
in class AbstractCorrelationDistanceFunction<O extends RealVector<O,?>,P extends Preprocessor<O>,PreferenceVectorBasedCorrelationDistance>
v1
- first RealVectorv2
- second RealVector
AbstractCorrelationDistanceFunction.correlationDistance(de.lmu.ifi.dbs.elki.data.RealVector,de.lmu.ifi.dbs.elki.data.RealVector)
public abstract PreferenceVectorBasedCorrelationDistance correlationDistance(O v1, O v2, BitSet pv1, BitSet pv2)
v1
- first RealVectorv2
- second RealVectorpv1
- the first preference vectorpv2
- the second preference vector
public double weightedDistance(O dv1, O dv2, BitSet weightVector)
dv1
- the first vectordv2
- the second vectorweightVector
- the preference vector
public double weightedDistance(Integer id1, Integer id2, BitSet weightVector)
id1
- the id of the first vectorid2
- the id of the second vectorweightVector
- the preference vector
public double weightedPrefereneceVectorDistance(O rv1, O rv2)
rv1
- the first vectorrv2
- the the second vector
public double weightedPrefereneceVectorDistance(Integer id1, Integer id2)
id1
- the id of the first vectorid2
- the id of the second vector
public String[] setParameters(String[] args) throws ParameterException
setParameters
in interface Parameterizable
setParameters
in class AbstractPreprocessorBasedDistanceFunction<O extends RealVector<O,?>,P extends Preprocessor<O>,PreferenceVectorBasedCorrelationDistance>
args
- parameters to set the attributes accordingly to
ParameterException
- in case of wrong parameter-settingParameterizable.setParameters(String[])
public double getEpsilon()
final AssociationID getAssociationID()
getAssociationID
in class AbstractCorrelationDistanceFunction<O extends RealVector<O,?>,P extends Preprocessor<O>,PreferenceVectorBasedCorrelationDistance>
final Class<PreferenceVectorPreprocessor> getPreprocessorSuperClassName()
getPreprocessorSuperClassName
in class AbstractCorrelationDistanceFunction<O extends RealVector<O,?>,P extends Preprocessor<O>,PreferenceVectorBasedCorrelationDistance>
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