O - the type of objects handled by this algorithm@Title(value="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") @Alias(value="de.lmu.ifi.dbs.elki.algorithm.outlier.LDF") public class LDF<O extends NumberVector> extends AbstractDistanceBasedAlgorithm<O,OutlierResult> implements OutlierAlgorithm
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
| Modifier and Type | Class and Description |
|---|---|
static class |
LDF.Parameterizer<O extends NumberVector>
Parameterization class.
|
| Modifier and Type | Field and Description |
|---|---|
protected double |
c
Scaling constant, to limit value range to 1/c
|
protected double |
h
Bandwidth scaling factor.
|
protected int |
k
Parameter k.
|
private KernelDensityFunction |
kernel
Kernel density function
|
private static Logging |
LOG
The logger for this class.
|
ALGORITHM_IDDISTANCE_FUNCTION_ID| Constructor and Description |
|---|
LDF(int k,
DistanceFunction<? super O> distance,
KernelDensityFunction kernel,
double h,
double c)
Constructor.
|
| Modifier and Type | Method and Description |
|---|---|
TypeInformation[] |
getInputTypeRestriction()
Get the input type restriction used for negotiating the data query.
|
protected Logging |
getLogger()
Get the (STATIC) logger for this class.
|
OutlierResult |
run(Database database,
Relation<O> relation)
Run the naive kernel density LOF algorithm.
|
getDistanceFunctionrunclone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, waitrunprivate static final Logging LOG
protected int k
protected double h
protected double c
private KernelDensityFunction kernel
public LDF(int k,
DistanceFunction<? super O> distance,
KernelDensityFunction kernel,
double h,
double c)
k - the value of kkernel - Kernel functionh - Kernel bandwidth scalingc - Score scaling parameterpublic OutlierResult run(Database database, Relation<O> relation)
database - Database to queryrelation - Data to processpublic TypeInformation[] getInputTypeRestriction()
AbstractAlgorithmgetInputTypeRestriction in interface AlgorithmgetInputTypeRestriction in class AbstractAlgorithm<OutlierResult>protected Logging getLogger()
AbstractAlgorithmgetLogger in class AbstractAlgorithm<OutlierResult>Copyright © 2019 ELKI Development Team. License information.