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

Class FastABOD<V extends NumberVector>

java.lang.Object

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

de.lmu.ifi.dbs.elki.algorithm.outlier.anglebased.ABOD<V>

de.lmu.ifi.dbs.elki.algorithm.outlier.anglebased.FastABOD<V>

Type Parameters:

V - Vector type

All Implemented Interfaces:

Algorithm, OutlierAlgorithm

Direct Known Subclasses:

LBABOD

@Title(value="Approximate ABOD: Angle-Based Outlier Detection")
 @Description(value="Outlier detection using variance analysis on angles, especially for high dimensional data sets.")
 @Reference(authors="Hans-Peter Kriegel, Matthias Schubert, Arthur Zimek",
           title="Angle-Based Outlier Detection in High-dimensional Data",
           booktitle="Proc. 14th ACM SIGKDD Int. Conf. Knowledge Discovery and Data Mining (KDD\'08)",
           url="https://doi.org/10.1145/1401890.1401946",
           bibkey="DBLP:conf/kdd/KriegelSZ08")
 @Alias(value={"de.lmu.ifi.dbs.elki.algorithm.outlier.FastABOD","fastabod"})
public class FastABOD<V extends NumberVector>
extends ABOD<V>

Fast-ABOD (approximateABOF) version of Angle-Based Outlier Detection / Angle-Based Outlier Factor.

Note: the minimum k is 3. The 2 nearest neighbors yields one 1 angle, which implies a constant 0 variance everywhere.

Reference:

Hans-Peter Kriegel, Matthias Schubert, Arthur Zimek
Angle-Based Outlier Detection in High-dimensional Data
Proc. 14th ACM SIGKDD Int. Conf. Knowledge Discovery and Data Mining (KDD'08)

Since:

0.6.0

Author:

Matthias Schubert (Original Code), Erich Schubert (ELKIfication)

Nested Class Summary

Nested Classes

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

Field Summary

Fields

Modifier and Type	Field and Description
protected int	k Number of nearest neighbors.
private static Logging	LOG The logger for this class.

Fields inherited from class de.lmu.ifi.dbs.elki.algorithm.outlier.anglebased.ABOD

kernelFunction

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

ALGORITHM_ID

Constructor Summary

Constructors

Constructor and Description
FastABOD(SimilarityFunction<? super V> kernelFunction, int k) Constructor for Angle-Based Outlier Detection (ABOD).

Method Summary

Modifier and Type	Method and Description
private void	fastABOD(Database db, Relation<V> relation, DBIDs ids, WritableDoubleDataStore abodvalues, DoubleMinMax minmaxabod) Full kernel-based version.
TypeInformation[]	getInputTypeRestriction() Get the input type restriction used for negotiating the data query.
protected Logging	getLogger() Get the (STATIC) logger for this class.
private boolean	kNNABOD(Database db, Relation<V> relation, DBIDs ids, WritableDoubleDataStore abodvalues, DoubleMinMax minmaxabod) Simpler kNN based, can use more indexing.
OutlierResult	run(Database db, Relation<V> relation) Run Fast-ABOD on the data set.

Methods inherited from class de.lmu.ifi.dbs.elki.algorithm.outlier.anglebased.ABOD

computeABOF

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.outlier.OutlierAlgorithm

run

Field Detail

LOG

private static final Logging LOG

The logger for this class.

k

protected int k

Number of nearest neighbors.

Constructor Detail

FastABOD

public FastABOD(SimilarityFunction<? super V> kernelFunction,
                int k)

Constructor for Angle-Based Outlier Detection (ABOD).

Parameters:

kernelFunction - kernel function to use

k - Number of nearest neighbors

Method Detail

run

public OutlierResult run(Database db,
                         Relation<V> relation)

Run Fast-ABOD on the data set.

Overrides:

run in class ABOD<V extends NumberVector>

Parameters:

relation - Relation to process

Returns:

Outlier detection result

kNNABOD

private boolean kNNABOD(Database db,
                        Relation<V> relation,
                        DBIDs ids,
                        WritableDoubleDataStore abodvalues,
                        DoubleMinMax minmaxabod)

Simpler kNN based, can use more indexing.

Parameters:

db - Database

relation - Data relation

ids - IDs

abodvalues - Score storage

minmaxabod - Min/max storage

Returns:

true if kNN were available and usable.

fastABOD

private void fastABOD(Database db,
                      Relation<V> relation,
                      DBIDs ids,
                      WritableDoubleDataStore abodvalues,
                      DoubleMinMax minmaxabod)

Full kernel-based version.

Parameters:

db - Database

relation - Data relation

ids - IDs

abodvalues - Score storage

minmaxabod - Min/max storage

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

Overrides:

getInputTypeRestriction in class ABOD<V extends NumberVector>

Returns:

Type restriction

getLogger

protected Logging getLogger()

Description copied from class: AbstractAlgorithm

Get the (STATIC) logger for this class.

Overrides:

getLogger in class ABOD<V extends NumberVector>

Returns:

the static logger