de.lmu.ifi.dbs.elki.algorithm

Class DependencyDerivator<V extends NumberVector>

java.lang.Object

de.lmu.ifi.dbs.elki.algorithm.AbstractAlgorithm<R>

de.lmu.ifi.dbs.elki.algorithm.AbstractNumberVectorDistanceBasedAlgorithm<V,CorrelationAnalysisSolution<V>>

de.lmu.ifi.dbs.elki.algorithm.DependencyDerivator<V>

Type Parameters:

V - the type of FeatureVector handled by this Algorithm

All Implemented Interfaces:

Algorithm, DistanceBasedAlgorithm<V>

@Title(value="Dependency Derivator: Deriving numerical inter-dependencies on data")
 @Description(value="Derives an equality-system describing dependencies between attributes in a correlation-cluster")
 @Reference(authors="Elke Achtert, Christian B\u00f6hm, Hans-Peter Kriegel, Peer Kr\u00f6ger, Arthur Zimek",
           title="Deriving Quantitative Dependencies for Correlation Clusters",
           booktitle="Proc. 12th Int. Conf. on Knowledge Discovery and Data Mining (KDD \'06)",
           url="https://doi.org/10.1145/1150402.1150408",
           bibkey="DBLP:conf/kdd/AchtertBKKZ06")
 @Priority(value=-5)
public class DependencyDerivator<V extends NumberVector>
extends AbstractNumberVectorDistanceBasedAlgorithm<V,CorrelationAnalysisSolution<V>>

Dependency derivator computes quantitatively linear dependencies among attributes of a given dataset based on a linear correlation PCA.

Reference:

Elke Achtert, Christian Böhm, Hans-Peter Kriegel, Peer Kröger, Arthur Zimek
Deriving Quantitative Dependencies for Correlation Clusters
Proc. 12th Int. Conf. on Knowledge Discovery and Data Mining (KDD '06)

Since:

0.1

Author:

Arthur Zimek

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	DependencyDerivator.Parameterizer<V extends NumberVector> Parameterization class.

Field Summary

Fields

Modifier and Type	Field and Description
private EigenPairFilter	filter Filter to select eigenvectors.
private static Logging	LOG The logger for this class.
private java.text.NumberFormat	nf Number format for output of solution.
private PCARunner	pca Holds the object performing the pca.
private boolean	randomsample Flag for random sampling vs. kNN
private int	sampleSize Holds the value of DependencyDerivator.Parameterizer.SAMPLE_SIZE_ID.

Fields inherited from class de.lmu.ifi.dbs.elki.algorithm.AbstractNumberVectorDistanceBasedAlgorithm

distanceFunction

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

ALGORITHM_ID

Fields inherited from interface de.lmu.ifi.dbs.elki.algorithm.DistanceBasedAlgorithm

DISTANCE_FUNCTION_ID

Constructor Summary

Constructors

Constructor and Description
DependencyDerivator(NumberVectorDistanceFunction<? super V> distanceFunction, java.text.NumberFormat nf, PCARunner pca, EigenPairFilter filter, int sampleSize, boolean randomsample) Constructor.

Method Summary

Modifier and Type	Method and Description
CorrelationAnalysisSolution<V>	generateModel(Relation<V> db, DBIDs ids) Runs the pca on the given set of IDs.
CorrelationAnalysisSolution<V>	generateModel(Relation<V> relation, DBIDs ids, double[] centroid) Runs the pca on the given set of IDs and for the given centroid.
TypeInformation[]	getInputTypeRestriction() Get the input type restriction used for negotiating the data query.
protected Logging	getLogger() Get the (STATIC) logger for this class.
CorrelationAnalysisSolution<V>	run(Database database, Relation<V> relation) Computes quantitatively linear dependencies among the attributes of the given database based on a linear correlation PCA.

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

getDistanceFunction

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

run

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

run

Field Detail

LOG

private static final Logging LOG

The logger for this class.

sampleSize

private final int sampleSize

Holds the value of DependencyDerivator.Parameterizer.SAMPLE_SIZE_ID.

pca

private final PCARunner pca

Holds the object performing the pca.

filter

private final EigenPairFilter filter

Filter to select eigenvectors.

nf

private final java.text.NumberFormat nf

Number format for output of solution.

randomsample

private final boolean randomsample

Flag for random sampling vs. kNN

Constructor Detail

DependencyDerivator

public DependencyDerivator(NumberVectorDistanceFunction<? super V> distanceFunction,
                           java.text.NumberFormat nf,
                           PCARunner pca,
                           EigenPairFilter filter,
                           int sampleSize,
                           boolean randomsample)

Constructor.

Parameters:

distanceFunction - distance function

nf - Number format

pca - PCA runner

filter - Eigenvector filter

sampleSize - sample size

randomsample - flag for random sampling

Method Detail

run

public CorrelationAnalysisSolution<V> run(Database database,
                                          Relation<V> relation)

Computes quantitatively linear dependencies among the attributes of the given database based on a linear correlation PCA.

Parameters:

database - the database to run this DependencyDerivator on

relation - the relation to use

Returns:

the CorrelationAnalysisSolution computed by this DependencyDerivator

generateModel

public CorrelationAnalysisSolution<V> generateModel(Relation<V> db,
                                                    DBIDs ids)

Runs the pca on the given set of IDs. The centroid is computed from the given ids.

Parameters:

db - the database

ids - the set of ids

Returns:

a matrix of equations describing the dependencies

generateModel

public CorrelationAnalysisSolution<V> generateModel(Relation<V> relation,
                                                    DBIDs ids,
                                                    double[] centroid)

Runs the pca on the given set of IDs and for the given centroid.

Parameters:

relation - the database

ids - the set of ids

centroid - the centroid

Returns:

a matrix of equations describing the dependencies

getInputTypeRestriction

public TypeInformation[] getInputTypeRestriction()

Description copied from class: AbstractAlgorithm

Get the input type restriction used for negotiating the data query.

Specified by:

getInputTypeRestriction in interface Algorithm

Specified by:

getInputTypeRestriction in class AbstractAlgorithm<CorrelationAnalysisSolution<V extends NumberVector>>

Returns:

Type restriction

getLogger

protected Logging getLogger()

Description copied from class: AbstractAlgorithm

Get the (STATIC) logger for this class.

Specified by:

getLogger in class AbstractAlgorithm<CorrelationAnalysisSolution<V extends NumberVector>>

Returns:

the static logger