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java.lang.Object de.lmu.ifi.dbs.elki.algorithm.AbstractAlgorithm<R> de.lmu.ifi.dbs.elki.algorithm.AbstractDistanceBasedAlgorithm<O,D,OutlierResult> de.lmu.ifi.dbs.elki.algorithm.outlier.KNNWeightOutlier<O,D>
O
- the type of DatabaseObjects handled by this AlgorithmD
- the type of Distance used by this Algorithm@Title(value="KNNWeight outlier detection") @Description(value="Outlier Detection based on the distances of an object to its k nearest neighbors.") @Reference(authors="F. Angiulli, C. Pizzuti", title="Fast Outlier Detection in High Dimensional Spaces", booktitle="Proc. European Conference on Principles of Knowledge Discovery and Data Mining (PKDD\'02), Helsinki, Finland, 2002", url="http://dx.doi.org/10.1007/3-540-45681-3_2") public class KNNWeightOutlier<O,D extends NumberDistance<D,?>>
Outlier Detection based on the accumulated distances of a point to its k nearest neighbors. Based on: F. Angiulli, C. Pizzuti: Fast Outlier Detection in High Dimensional Spaces. In: Proc. European Conference on Principles of Knowledge Discovery and Data Mining (PKDD'02), Helsinki, Finland, 2002.
Nested Class Summary | |
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static class |
KNNWeightOutlier.Parameterizer<O,D extends NumberDistance<D,?>>
Parameterization class. |
Field Summary | |
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private int |
k
Holds the value of K_ID . |
static OptionID |
K_ID
Parameter to specify the k nearest neighbor |
static OptionID |
KNNQUERY_ID
The kNN query used. |
private static Logging |
logger
The logger for this class. |
Fields inherited from class de.lmu.ifi.dbs.elki.algorithm.AbstractDistanceBasedAlgorithm |
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DISTANCE_FUNCTION_ID |
Constructor Summary | |
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KNNWeightOutlier(DistanceFunction<? super O,D> distanceFunction,
int k)
Constructor with parameters. |
Method Summary | |
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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 algorithm in the timed evaluation part. |
Methods inherited from class de.lmu.ifi.dbs.elki.algorithm.AbstractDistanceBasedAlgorithm |
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getDistanceFunction |
Methods inherited from class de.lmu.ifi.dbs.elki.algorithm.AbstractAlgorithm |
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makeParameterDistanceFunction, run |
Methods inherited from class java.lang.Object |
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clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
Methods inherited from interface de.lmu.ifi.dbs.elki.algorithm.outlier.OutlierAlgorithm |
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run |
Field Detail |
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private static final Logging logger
public static final OptionID K_ID
public static final OptionID KNNQUERY_ID
private int k
K_ID
.
Constructor Detail |
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public KNNWeightOutlier(DistanceFunction<? super O,D> distanceFunction, int k)
distanceFunction
- Distance functionk
- k ParameterMethod Detail |
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public OutlierResult run(Database database, Relation<O> relation)
public 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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