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Packages that use IntegerDistance | |
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de.lmu.ifi.dbs.elki.algorithm.clustering | Clustering algorithms
Clustering algorithms are supposed to implement the Algorithm -Interface. |
de.lmu.ifi.dbs.elki.algorithm.clustering.correlation | Correlation clustering algorithms |
de.lmu.ifi.dbs.elki.algorithm.outlier | Outlier detection algorithms |
de.lmu.ifi.dbs.elki.distance.distancevalue | Distance values, i.e. object storing an actual distance value along with comparison functions and value parsers. |
de.lmu.ifi.dbs.elki.distance.similarityfunction | Similarity functions. |
Uses of IntegerDistance in de.lmu.ifi.dbs.elki.algorithm.clustering |
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Fields in de.lmu.ifi.dbs.elki.algorithm.clustering declared as IntegerDistance | |
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private IntegerDistance |
SNNClustering.epsilon
Holds the value of SNNClustering.EPSILON_ID . |
protected IntegerDistance |
SNNClustering.Parameterizer.epsilon
|
Method parameters in de.lmu.ifi.dbs.elki.algorithm.clustering with type arguments of type IntegerDistance | |
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protected void |
SNNClustering.expandCluster(SimilarityQuery<O,IntegerDistance> snnInstance,
DBID startObjectID,
FiniteProgress objprog,
IndefiniteProgress clusprog)
DBSCAN-function expandCluster adapted to SNN criterion. |
protected List<DBID> |
SNNClustering.findSNNNeighbors(SimilarityQuery<O,IntegerDistance> snnInstance,
DBID queryObject)
Returns the shared nearest neighbors of the specified query object in the given database. |
Constructors in de.lmu.ifi.dbs.elki.algorithm.clustering with parameters of type IntegerDistance | |
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SNNClustering(SharedNearestNeighborSimilarityFunction<O> similarityFunction,
IntegerDistance epsilon,
int minpts)
Constructor. |
Uses of IntegerDistance in de.lmu.ifi.dbs.elki.algorithm.clustering.correlation |
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Fields in de.lmu.ifi.dbs.elki.algorithm.clustering.correlation with type parameters of type IntegerDistance | |
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protected COPAC<V,IntegerDistance> |
ERiC.Parameterizer.copac
The COPAC instance to use |
private COPAC<V,IntegerDistance> |
ERiC.copacAlgorithm
The COPAC clustering algorithm. |
Method parameters in de.lmu.ifi.dbs.elki.algorithm.clustering.correlation with type arguments of type IntegerDistance | |
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private void |
ERiC.buildHierarchy(SortedMap<Integer,List<Cluster<CorrelationModel<V>>>> clusterMap,
DistanceQuery<V,IntegerDistance> query)
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Constructor parameters in de.lmu.ifi.dbs.elki.algorithm.clustering.correlation with type arguments of type IntegerDistance | |
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ERiC(COPAC<V,IntegerDistance> copacAlgorithm)
Constructor. |
Uses of IntegerDistance in de.lmu.ifi.dbs.elki.algorithm.outlier |
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Method parameters in de.lmu.ifi.dbs.elki.algorithm.outlier with type arguments of type IntegerDistance | |
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private KNNList<DoubleDistance> |
SOD.getKNN(Relation<V> database,
SimilarityQuery<V,IntegerDistance> snnInstance,
DBID queryObject)
Provides the k nearest neighbors in terms of the shared nearest neighbor distance. |
Uses of IntegerDistance in de.lmu.ifi.dbs.elki.distance.distancevalue |
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Fields in de.lmu.ifi.dbs.elki.distance.distancevalue declared as IntegerDistance | |
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static IntegerDistance |
IntegerDistance.FACTORY
The static factory instance |
Methods in de.lmu.ifi.dbs.elki.distance.distancevalue that return IntegerDistance | |
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IntegerDistance |
IntegerDistance.fromDouble(double val)
|
IntegerDistance |
IntegerDistance.infiniteDistance()
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IntegerDistance |
IntegerDistance.minus(IntegerDistance distance)
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IntegerDistance |
IntegerDistance.nullDistance()
|
IntegerDistance |
IntegerDistance.parseString(String val)
|
IntegerDistance |
IntegerDistance.plus(IntegerDistance distance)
|
IntegerDistance |
IntegerDistance.undefinedDistance()
|
Methods in de.lmu.ifi.dbs.elki.distance.distancevalue with parameters of type IntegerDistance | |
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int |
IntegerDistance.compareTo(IntegerDistance other)
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IntegerDistance |
IntegerDistance.minus(IntegerDistance distance)
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IntegerDistance |
IntegerDistance.plus(IntegerDistance distance)
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Uses of IntegerDistance in de.lmu.ifi.dbs.elki.distance.similarityfunction |
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Methods in de.lmu.ifi.dbs.elki.distance.similarityfunction that return IntegerDistance | |
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IntegerDistance |
SharedNearestNeighborSimilarityFunction.getDistanceFactory()
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IntegerDistance |
SharedNearestNeighborSimilarityFunction.Instance.getDistanceFactory()
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IntegerDistance |
SharedNearestNeighborSimilarityFunction.Instance.similarity(DBID id1,
DBID id2)
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