Package | Description |
---|---|
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.
|
Modifier and Type | Field and Description |
---|---|
private IntegerDistance |
SNNClustering.epsilon
Holds the value of
SNNClustering.EPSILON_ID . |
protected IntegerDistance |
SNNClustering.Parameterizer.epsilon |
Modifier and Type | Method and Description |
---|---|
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.
|
Constructor and Description |
---|
SNNClustering(SharedNearestNeighborSimilarityFunction<O> similarityFunction,
IntegerDistance epsilon,
int minpts)
Constructor.
|
Modifier and Type | Field and Description |
---|---|
protected COPAC<V,IntegerDistance> |
ERiC.Parameterizer.copac
The COPAC instance to use
|
private COPAC<V,IntegerDistance> |
ERiC.copacAlgorithm
The COPAC clustering algorithm.
|
Modifier and Type | Method and Description |
---|---|
private void |
ERiC.buildHierarchy(SortedMap<Integer,List<Cluster<CorrelationModel<V>>>> clusterMap,
DistanceQuery<V,IntegerDistance> query) |
Constructor and Description |
---|
ERiC(COPAC<V,IntegerDistance> copacAlgorithm)
Constructor.
|
Modifier and Type | Method and Description |
---|---|
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.
|
Modifier and Type | Field and Description |
---|---|
static IntegerDistance |
IntegerDistance.FACTORY
The static factory instance
|
Modifier and Type | Method and Description |
---|---|
IntegerDistance |
IntegerDistance.fromDouble(double val) |
IntegerDistance |
IntegerDistance.infiniteDistance() |
IntegerDistance |
IntegerDistance.minus(IntegerDistance distance) |
IntegerDistance |
IntegerDistance.nullDistance() |
IntegerDistance |
IntegerDistance.parseString(String val) |
IntegerDistance |
IntegerDistance.plus(IntegerDistance distance) |
IntegerDistance |
IntegerDistance.undefinedDistance() |
Modifier and Type | Method and Description |
---|---|
int |
IntegerDistance.compareTo(IntegerDistance other) |
IntegerDistance |
IntegerDistance.minus(IntegerDistance distance) |
IntegerDistance |
IntegerDistance.plus(IntegerDistance distance) |
Modifier and Type | Method and Description |
---|---|
IntegerDistance |
SharedNearestNeighborSimilarityFunction.getDistanceFactory() |
IntegerDistance |
SharedNearestNeighborSimilarityFunction.Instance.getDistanceFactory() |
IntegerDistance |
SharedNearestNeighborSimilarityFunction.Instance.similarity(DBID id1,
DBID id2) |