O
- Object type@Title(value="IDOS: Intrinsic Dimensional Outlier Score") @Reference(authors="Jonathan von Br\u00fcnken, Michael E. Houle, Arthur Zimek", title="Intrinsic Dimensional Outlier Detection in High-Dimensional Data", booktitle="NII Technical Report (NII-2015-003E)", url="http://www.nii.ac.jp/TechReports/15-003E.html", bibkey="tr/nii/BrunkenHZ15") public class IDOS<O> extends AbstractDistanceBasedAlgorithm<O,OutlierResult> implements OutlierAlgorithm
Reference:
Jonathan von Brünken, Michael E. Houle, Arthur Zimek
Intrinsic Dimensional Outlier Detection in High-Dimensional Data
NII Technical Report (NII-2015-003E)
Modifier and Type | Class and Description |
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static class |
IDOS.Parameterizer<O>
Parameterization class.
|
Modifier and Type | Field and Description |
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protected IntrinsicDimensionalityEstimator |
estimator
Estimator for intrinsic dimensionality.
|
protected int |
k_c
kNN for the context set (ID computation).
|
protected int |
k_r
kNN for the reference set.
|
private static Logging |
LOG
The logger for this class.
|
ALGORITHM_ID
DISTANCE_FUNCTION_ID
Constructor and Description |
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IDOS(DistanceFunction<? super O> distanceFunction,
IntrinsicDimensionalityEstimator estimator,
int kc,
int kr)
Constructor.
|
Modifier and Type | Method and Description |
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protected DoubleDataStore |
computeIDOS(DBIDs ids,
KNNQuery<O> knnQ,
DoubleDataStore intDims,
DoubleMinMax idosminmax)
Computes all IDOS scores.
|
protected DoubleDataStore |
computeIDs(DBIDs ids,
KNNQuery<O> knnQ)
Computes all IDs
|
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 algorithm
|
getDistanceFunction
run
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
run
private static final Logging LOG
protected int k_c
protected int k_r
protected IntrinsicDimensionalityEstimator estimator
public IDOS(DistanceFunction<? super O> distanceFunction, IntrinsicDimensionalityEstimator estimator, int kc, int kr)
distanceFunction
- the distance function to useestimator
- Estimator for intrinsic dimensionalitykc
- the context set size for the ID computationkr
- the neighborhood size to use in score computationpublic OutlierResult run(Database database, Relation<O> relation)
database
- Databaserelation
- Data relationprotected DoubleDataStore computeIDs(DBIDs ids, KNNQuery<O> knnQ)
ids
- the DBIDs to processknnQ
- the KNN queryprotected DoubleDataStore computeIDOS(DBIDs ids, KNNQuery<O> knnQ, DoubleDataStore intDims, DoubleMinMax idosminmax)
ids
- the DBIDs to processknnQ
- the KNN queryintDims
- Precomputed intrinsic dimensionalitiesidosminmax
- Output of minimum and maximum, for metadatapublic TypeInformation[] getInputTypeRestriction()
AbstractAlgorithm
getInputTypeRestriction
in interface Algorithm
getInputTypeRestriction
in class AbstractAlgorithm<OutlierResult>
protected Logging getLogger()
AbstractAlgorithm
getLogger
in class AbstractAlgorithm<OutlierResult>
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