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Packages that use AbstractAlgorithm | |
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de.lmu.ifi.dbs.elki.algorithm | Package to collect algorithms suitable as a task for the KDDTask main routine. |
de.lmu.ifi.dbs.elki.algorithm.clustering | Package collects clustering algorithms. |
de.lmu.ifi.dbs.elki.algorithm.clustering.biclustering | Package to collect biclustering algorithms suitable as a task for the KDDTask main routine. |
de.lmu.ifi.dbs.elki.algorithm.clustering.correlation | Package to collect correlation clustering algorithms suitable as a task for the KDDTask main routine. |
de.lmu.ifi.dbs.elki.algorithm.clustering.subspace | Package to collect algorithms for clustering in axis-parallel subspaces, suitable as a task for the KDDTask main routine. |
Uses of AbstractAlgorithm in de.lmu.ifi.dbs.elki.algorithm |
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Subclasses of AbstractAlgorithm in de.lmu.ifi.dbs.elki.algorithm | |
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APRIORI
Provides the APRIORI algorithm for Mining Association Rules. |
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DependencyDerivator<V extends RealVector<V,?>,D extends Distance<D>>
Dependency derivator computes quantitativly linear dependencies among attributes of a given dataset based on a linear correlation PCA. |
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DistanceBasedAlgorithm<O extends DatabaseObject,D extends Distance<D>>
Provides an abstract algorithm already setting the distance function. |
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KNNDistanceOrder<O extends DatabaseObject,D extends Distance<D>>
Provides an order of the kNN-distances for all objects within the database. |
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KNNJoin<V extends NumberVector<V,?>,D extends Distance<D>,N extends SpatialNode<N,E>,E extends SpatialEntry>
Joins in a given spatial database to each object its k-nearest neighbors. |
Uses of AbstractAlgorithm in de.lmu.ifi.dbs.elki.algorithm.clustering |
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Subclasses of AbstractAlgorithm in de.lmu.ifi.dbs.elki.algorithm.clustering | |
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DBSCAN<O extends DatabaseObject,D extends Distance<D>>
DBSCAN provides the DBSCAN algorithm, an algorithm to find density-connected sets in a database. |
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DeLiClu<O extends NumberVector<O,?>,D extends Distance<D>>
DeLiClu provides the DeLiClu algorithm, a hierachical algorithm to find density-connected sets in a database. |
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EM<V extends RealVector<V,?>>
Provides the EM algorithm (clustering by expectation maximization). |
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KMeans<D extends Distance<D>,V extends RealVector<V,?>>
Provides the k-means algorithm. |
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OPTICS<O extends DatabaseObject,D extends Distance<D>>
OPTICS provides the OPTICS algorithm. |
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ProjectedDBSCAN<V extends RealVector<V,?>>
Provides an abstract algorithm requiring a VarianceAnalysisPreprocessor. |
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SLINK<O extends DatabaseObject,D extends Distance<D>>
Efficient implementation of the Single-Link Algorithm SLINK of R. |
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SNNClustering<O extends DatabaseObject,D extends Distance<D>>
Shared nearest neighbor clustering. |
Uses of AbstractAlgorithm in de.lmu.ifi.dbs.elki.algorithm.clustering.biclustering |
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Subclasses of AbstractAlgorithm in de.lmu.ifi.dbs.elki.algorithm.clustering.biclustering | |
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AbstractBiclustering<V extends RealVector<V,Double>>
Abstract class as a convenience for different biclustering approaches. |
Uses of AbstractAlgorithm in de.lmu.ifi.dbs.elki.algorithm.clustering.correlation |
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Subclasses of AbstractAlgorithm in de.lmu.ifi.dbs.elki.algorithm.clustering.correlation | |
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CASH
Subspace clustering algorithm based on the hough transform. |
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COPAA<V extends RealVector<V,?>>
Algorithm to partition a database according to the correlation dimension of its objects and to then perform an arbitrary algorithm over the partitions. |
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COPAC<V extends RealVector<V,?>>
Algorithm to partition a database according to the correlation dimension of its objects and to then perform an arbitrary clustering algorithm over the partitions. |
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ERiC<V extends RealVector<V,?>>
Performs correlation clustering on the data partitioned according to local correlation dimensionality and builds a hierarchy of correlation clusters that allows multiple inheritance from the clustering result. |
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FourC<O extends RealVector<O,?>>
4C identifies local subgroups of data objects sharing a uniform correlation. |
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ORCLUS<V extends RealVector<V,?>>
ORCLUS provides the ORCLUS algorithm. |
Uses of AbstractAlgorithm in de.lmu.ifi.dbs.elki.algorithm.clustering.subspace |
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Subclasses of AbstractAlgorithm in de.lmu.ifi.dbs.elki.algorithm.clustering.subspace | |
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CLIQUE<V extends RealVector<V,?>>
Implementation of the CLIQUE algorithm, a grid-based algorithm to identify dense clusters in subspaces of maximum dimensionality. |
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DiSH<V extends RealVector<V,?>>
Algorithm for detecting subspace hierarchies. |
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PreDeCon<V extends RealVector<V,?>>
PreDeCon computes clusters of subspace preference weighted connected points. |
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PROCLUS<V extends RealVector<V,?>>
PROCLUS provides the PROCLUS algorithm. |
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ProjectedClustering<V extends RealVector<V,?>>
Abstract superclass for PROCLUS and ORCLUS. |
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