
O - the type of data objects handled by this algorithm@Title(value="LOF: Local Outlier Factor") @Description(value="Algorithm to compute density-based local outlier factors in a database based on the neighborhood size parameter \'k\'") @Reference(authors="M. M. Breunig, H.-P. Kriegel, R. Ng, and J. Sander", title="LOF: Identifying Density-Based Local Outliers", booktitle="Proc. 2nd ACM SIGMOD Int. Conf. on Management of Data (SIGMOD \'00), Dallas, TX, 2000", url="http://dx.doi.org/10.1145/342009.335388") @Alias(value={"de.lmu.ifi.dbs.elki.algorithm.outlier.LOF","LOF"}) public class LOF<O> extends AbstractDistanceBasedAlgorithm<O,OutlierResult> implements OutlierAlgorithm
Algorithm to compute density-based local outlier factors in a database based
on a specified parameter LOF.Parameterizer.K_ID (-lof.k).
The original LOF parameter was called "minPts", but for consistency within ELKI we have renamed this parameter to "k".
Compatibility note: as of ELKI 0.7.0, we no longer include the query point, for consistency with other methods.
Reference:
M. M. Breunig, H.-P. Kriegel, R. Ng, J. Sander:
LOF: Identifying Density-Based Local Outliers.
In: Proc. 2nd ACM SIGMOD Int. Conf. on Management of Data (SIGMOD'00),
Dallas, TX, 2000.
| Modifier and Type | Class and Description |
|---|---|
static class |
LOF.Parameterizer<O>
Parameterization class.
|
| Modifier and Type | Field and Description |
|---|---|
protected int |
k
The number of neighbors to query (including the query point!)
|
private static Logging |
LOG
The logger for this class.
|
DISTANCE_FUNCTION_ID| Constructor and Description |
|---|
LOF(int k,
DistanceFunction<? super O> distanceFunction)
Constructor.
|
| Modifier and Type | Method and Description |
|---|---|
protected double |
computeLOFScore(KNNQuery<O> knnq,
DBIDRef cur,
DoubleDataStore lrds)
Compute a single LOF score.
|
private void |
computeLOFScores(KNNQuery<O> knnq,
DBIDs ids,
DoubleDataStore lrds,
WritableDoubleDataStore lofs,
DoubleMinMax lofminmax)
Compute local outlier factors.
|
protected double |
computeLRD(KNNQuery<O> knnq,
DBIDIter curr)
Compute a single local reachability distance.
|
private void |
computeLRDs(KNNQuery<O> knnq,
DBIDs ids,
WritableDoubleDataStore lrds)
Compute local reachability distances.
|
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)
Runs the LOF algorithm on the given database.
|
getDistanceFunctionmakeParameterDistanceFunction, runclone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, waitrunprivate static final Logging LOG
protected int k
public LOF(int k,
DistanceFunction<? super O> distanceFunction)
k - the number of neighbors to use for comparison (excluding the query
point)distanceFunction - the neighborhood distance functionpublic OutlierResult run(Database database, Relation<O> relation)
database - Database to queryrelation - Data to processprivate void computeLRDs(KNNQuery<O> knnq, DBIDs ids, WritableDoubleDataStore lrds)
knnq - KNN queryids - IDs to processlrds - Reachability storageprotected double computeLRD(KNNQuery<O> knnq, DBIDIter curr)
knnq - kNN Querycurr - Current objectprivate void computeLOFScores(KNNQuery<O> knnq, DBIDs ids, DoubleDataStore lrds, WritableDoubleDataStore lofs, DoubleMinMax lofminmax)
knnq - KNN queryids - IDs to processlrds - Local reachability distanceslofs - Local outlier factor storagelofminmax - Score minimum/maximum trackerprotected double computeLOFScore(KNNQuery<O> knnq, DBIDRef cur, DoubleDataStore lrds)
knnq - kNN querycur - Current objectlrds - Stored reachability densitiespublic TypeInformation[] getInputTypeRestriction()
AbstractAlgorithmgetInputTypeRestriction in interface AlgorithmgetInputTypeRestriction in class AbstractAlgorithm<OutlierResult>protected Logging getLogger()
AbstractAlgorithmgetLogger in class AbstractAlgorithm<OutlierResult>Copyright © 2015 ELKI Development Team, Lehr- und Forschungseinheit für Datenbanksysteme, Ludwig-Maximilians-Universität München. License information.