de.lmu.ifi.dbs.elki.algorithm.outlier.lof

Class INFLO<O>

java.lang.Object

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

de.lmu.ifi.dbs.elki.algorithm.AbstractDistanceBasedAlgorithm<O,OutlierResult>

de.lmu.ifi.dbs.elki.algorithm.outlier.lof.INFLO<O>

Type Parameters:

O - the type of DatabaseObject the algorithm is applied on

All Implemented Interfaces:

Algorithm, DistanceBasedAlgorithm<O>, OutlierAlgorithm

@Title(value="INFLO: Influenced Outlierness Factor")
@Description(value="Ranking Outliers Using Symmetric Neigborhood Relationship")
@Reference(authors="W. Jin, A. Tung, J. Han, and W. Wang",
           title="Ranking outliers using symmetric neighborhood relationship",
           booktitle="Proc. 10th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining",
           url="http://dx.doi.org/10.1007/11731139_68")
public class INFLO<O>
extends AbstractDistanceBasedAlgorithm<O,OutlierResult>
implements OutlierAlgorithm

Influence Outliers using Symmetric Relationship (INFLO) using two-way search, is an outlier detection method based on LOF; but also using the reverse kNN. Reference:

W. Jin, A. Tung, J. Han, and W. Wang
Ranking outliers using symmetric neighborhood relationship
Proc. 10th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining, 2006.

Author:

Ahmed Hettab, Erich Schubert

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	INFLO.Parameterizer<O> Parameterization class.

Field Summary

Fields

Modifier and Type	Field and Description
private int	k Number of neighbors to use.
private static Logging	LOG The logger for this class.
private double	m Pruning threshold m.

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

DISTANCE_FUNCTION_ID

Constructor Summary

Constructors

Constructor and Description
INFLO(DistanceFunction<? super O> distanceFunction, double m, int k) Constructor with parameters.

Method Summary

Methods

Modifier and Type	Method and Description
protected void	computeINFLO(Relation<O> relation, ModifiableDBIDs pruned, WritableDataStore<ModifiableDBIDs> knns, WritableDataStore<ModifiableDBIDs> rnns, WritableDoubleDataStore density, WritableDoubleDataStore inflos, DoubleMinMax inflominmax) Compute the final INFLO scores.
protected void	computeNeighborhoods(Relation<O> relation, KNNQuery<O> knnQuery, ModifiableDBIDs pruned, WritableDataStore<ModifiableDBIDs> knns, WritableDataStore<ModifiableDBIDs> rnns, WritableDoubleDataStore density) Compute neighborhoods
TypeInformation[]	getInputTypeRestriction() Get the input type restriction used for negotiating the data query.
protected DBIDs	getKNN(DBIDIter q, KNNQuery<O> knnQuery, WritableDataStore<ModifiableDBIDs> knns, WritableDoubleDataStore density) Get the (forward only) kNN of an object, including the query point
protected Logging	getLogger() Get the (STATIC) logger for this class.
OutlierResult	run(Database database, Relation<O> relation) Run the algorithm

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

getDistanceFunction

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

makeParameterDistanceFunction, 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.outlier.OutlierAlgorithm

run

Field Detail

LOG

private static final Logging LOG

The logger for this class.

m

private double m

Pruning threshold m.

k

private int k

Number of neighbors to use.

Constructor Detail

INFLO

public INFLO(DistanceFunction<? super O> distanceFunction,
     double m,
     int k)

Constructor with parameters.

Parameters:

distanceFunction - Distance function in use

m - m Parameter

k - k Parameter

Method Detail

run

public OutlierResult run(Database database,
                Relation<O> relation)

Run the algorithm

Parameters:

database - Database to process

relation - Relation to process

Returns:

Outlier result

computeNeighborhoods

protected void computeNeighborhoods(Relation<O> relation,
                        KNNQuery<O> knnQuery,
                        ModifiableDBIDs pruned,
                        WritableDataStore<ModifiableDBIDs> knns,
                        WritableDataStore<ModifiableDBIDs> rnns,
                        WritableDoubleDataStore density)

Compute neighborhoods

Parameters:

relation -

knnQuery -

pruned -

knns -

rnns -

density -

computeINFLO

protected void computeINFLO(Relation<O> relation,
                ModifiableDBIDs pruned,
                WritableDataStore<ModifiableDBIDs> knns,
                WritableDataStore<ModifiableDBIDs> rnns,
                WritableDoubleDataStore density,
                WritableDoubleDataStore inflos,
                DoubleMinMax inflominmax)

Compute the final INFLO scores.

Parameters:

relation - Data relation

pruned - Pruned objects

knns - kNN storage

rnns - reverse kNN storage

density - Density estimation

inflos - Inflo score storage

inflominmax - Output of minimum and maximum

getKNN

protected DBIDs getKNN(DBIDIter q,
           KNNQuery<O> knnQuery,
           WritableDataStore<ModifiableDBIDs> knns,
           WritableDoubleDataStore density)

Get the (forward only) kNN of an object, including the query point

Parameters:

q - Query point

knnQuery - Query function

knns - kNN storage

density - Density storage

Returns:

Neighbor list

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<OutlierResult>

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<OutlierResult>

Returns:

the static logger