Package elki.outlier.lof

Class LDF<O extends NumberVector>

java.lang.Object

elki.outlier.lof.LDF<O>

Type Parameters:

O - the type of objects handled by this algorithm

All Implemented Interfaces:

Algorithm, OutlierAlgorithm

@Title("LDF: Outlier Detection with Kernel Density Functions")
@Reference(authors="L. J. Latecki, A. Lazarevic, D. Pokrajac",
           title="Outlier Detection with Kernel Density Functions",
           booktitle="Machine Learning and Data Mining in Pattern Recognition",
           url="https://doi.org/10.1007/978-3-540-73499-4_6",
           bibkey="DBLP:conf/mldm/LateckiLP07")
public class LDF<O extends NumberVector>
extends java.lang.Object
implements OutlierAlgorithm

Outlier Detection with Kernel Density Functions.

A variation of LOF which uses kernel density estimation, but in contrast to SimpleKernelDensityLOF also uses the reachability concept of LOF.

Reference:

Outlier Detection with Kernel Density Functions
L. J. Latecki, A. Lazarevic, D. Pokrajac
Machine Learning and Data Mining in Pattern Recognition

Since:

0.5.5

Author:

Erich Schubert

Nested Class Summary

Nested classes/interfaces inherited from interface elki.Algorithm

Algorithm.Utils

Field Summary

Fields

Modifier and Type	Field	Description
protected double	c	Scaling constant, to limit value range to 1/c
protected Distance<? super O>	distance	Distance function used.
protected double	h	Bandwidth scaling factor.
protected KernelDensityFunction	kernel	Kernel density function
protected int	kplus	Parameter k + 1 for the query point.
private static Logging	LOG	The logger for this class.

Constructor Summary

Constructors

Constructor	Description
LDF(int k, Distance<? super O> distance, KernelDensityFunction kernel, double h, double c)	Constructor.

Method Summary

Modifier and Type	Method	Description
TypeInformation[]	getInputTypeRestriction()	Get the input type restriction used for negotiating the data query.
OutlierResult	run(Relation<O> relation)	Run the naive kernel density LOF algorithm.

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Methods inherited from interface elki.outlier.OutlierAlgorithm

autorun

Field Detail

LOG

private static final Logging LOG

The logger for this class.

distance

protected Distance<? super O extends NumberVector> distance

Distance function used.

kplus

protected int kplus

Parameter k + 1 for the query point.

h

protected double h

Bandwidth scaling factor.

c

protected double c

Scaling constant, to limit value range to 1/c

kernel

protected KernelDensityFunction kernel

Kernel density function

Constructor Detail

LDF

public LDF(int k,
           Distance<? super O> distance,
           KernelDensityFunction kernel,
           double h,
           double c)

Constructor.

Parameters:

k - the value of k

kernel - Kernel function

h - Kernel bandwidth scaling

c - Score scaling parameter

Method Detail

getInputTypeRestriction

public TypeInformation[] getInputTypeRestriction()

Description copied from interface: Algorithm

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

Specified by:

getInputTypeRestriction in interface Algorithm

Returns:

Type restriction

run

public OutlierResult run(Relation<O> relation)

Run the naive kernel density LOF algorithm.

Parameters:

relation - Data to process

Returns:

LOF outlier result