Uses of Package
de.lmu.ifi.dbs.elki.algorithm

Packages that use de.lmu.ifi.dbs.elki.algorithm
de.lmu.ifi.dbs.elki.algorithm Algorithms suitable as a task for the KDDTask main routine. 
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.clustering.subspace Axis-parallel subspace clustering algorithms The clustering algorithms in this package are instances of both, projected clustering algorithms or subspace clustering algorithms according to the classical but somewhat obsolete classification schema of clustering algorithms for axis-parallel subspaces. 
de.lmu.ifi.dbs.elki.algorithm.clustering.trivial Trivial clustering algorithms: all in one, no clusters, label clusterings These methods are mostly useful for providing a reference result in evaluation. 
de.lmu.ifi.dbs.elki.algorithm.outlier Outlier detection algorithms 
de.lmu.ifi.dbs.elki.algorithm.outlier.meta Meta outlier detection algorithms: external scores, score rescaling. 
de.lmu.ifi.dbs.elki.algorithm.outlier.spatial Spatial outlier detection algorithms 
de.lmu.ifi.dbs.elki.algorithm.outlier.trivial Trivial outlier detection algorithms: no outliers, all outliers, label outliers. 
de.lmu.ifi.dbs.elki.algorithm.statistics Statistical analysis algorithms The algorithms in this package perform statistical analysis of the data (e.g. compute distributions, distance distributions etc.) 
de.lmu.ifi.dbs.elki.workflow Work flow packages, e.g. following the usual KDD model, closely related to CRISP-DM 
 

Classes in de.lmu.ifi.dbs.elki.algorithm used by de.lmu.ifi.dbs.elki.algorithm
AbstractAlgorithm
           This class serves also as a model of implementing an algorithm within this framework.
AbstractDistanceBasedAlgorithm
          Provides an abstract algorithm already setting the distance function.
AbstractDistanceBasedAlgorithm.Parameterizer
          Parameterization helper class.
AbstractPrimitiveDistanceBasedAlgorithm
          Provides an abstract algorithm already setting the distance function.
AbstractPrimitiveDistanceBasedAlgorithm.Parameterizer
          Parameterization helper class.
Algorithm
           Specifies the requirements for any algorithm that is to be executable by the main class.
APRIORI
          Provides the APRIORI algorithm for Mining Association Rules.
DependencyDerivator
           Dependency derivator computes quantitatively linear dependencies among attributes of a given dataset based on a linear correlation PCA.
KNNDistanceOrder
          Provides an order of the kNN-distances for all objects within the database.
KNNJoin
          Joins in a given spatial database to each object its k-nearest neighbors.
MaterializeDistances
          Algorithm to materialize all the distances in a data set.
 

Classes in de.lmu.ifi.dbs.elki.algorithm used by de.lmu.ifi.dbs.elki.algorithm.clustering
AbstractAlgorithm
           This class serves also as a model of implementing an algorithm within this framework.
AbstractDistanceBasedAlgorithm
          Provides an abstract algorithm already setting the distance function.
AbstractDistanceBasedAlgorithm.Parameterizer
          Parameterization helper class.
AbstractPrimitiveDistanceBasedAlgorithm
          Provides an abstract algorithm already setting the distance function.
AbstractPrimitiveDistanceBasedAlgorithm.Parameterizer
          Parameterization helper class.
Algorithm
           Specifies the requirements for any algorithm that is to be executable by the main class.
KNNJoin
          Joins in a given spatial database to each object its k-nearest neighbors.
 

Classes in de.lmu.ifi.dbs.elki.algorithm used by de.lmu.ifi.dbs.elki.algorithm.clustering.correlation
AbstractAlgorithm
           This class serves also as a model of implementing an algorithm within this framework.
AbstractDistanceBasedAlgorithm
          Provides an abstract algorithm already setting the distance function.
Algorithm
           Specifies the requirements for any algorithm that is to be executable by the main class.
 

Classes in de.lmu.ifi.dbs.elki.algorithm used by de.lmu.ifi.dbs.elki.algorithm.clustering.subspace
AbstractAlgorithm
           This class serves also as a model of implementing an algorithm within this framework.
AbstractDistanceBasedAlgorithm
          Provides an abstract algorithm already setting the distance function.
Algorithm
           Specifies the requirements for any algorithm that is to be executable by the main class.
 

Classes in de.lmu.ifi.dbs.elki.algorithm used by de.lmu.ifi.dbs.elki.algorithm.clustering.trivial
AbstractAlgorithm
           This class serves also as a model of implementing an algorithm within this framework.
Algorithm
           Specifies the requirements for any algorithm that is to be executable by the main class.
 

Classes in de.lmu.ifi.dbs.elki.algorithm used by de.lmu.ifi.dbs.elki.algorithm.outlier
AbstractAlgorithm
           This class serves also as a model of implementing an algorithm within this framework.
AbstractDistanceBasedAlgorithm
          Provides an abstract algorithm already setting the distance function.
AbstractDistanceBasedAlgorithm.Parameterizer
          Parameterization helper class.
Algorithm
           Specifies the requirements for any algorithm that is to be executable by the main class.
 

Classes in de.lmu.ifi.dbs.elki.algorithm used by de.lmu.ifi.dbs.elki.algorithm.outlier.meta
AbstractAlgorithm
           This class serves also as a model of implementing an algorithm within this framework.
Algorithm
           Specifies the requirements for any algorithm that is to be executable by the main class.
 

Classes in de.lmu.ifi.dbs.elki.algorithm used by de.lmu.ifi.dbs.elki.algorithm.outlier.spatial
AbstractAlgorithm
           This class serves also as a model of implementing an algorithm within this framework.
AbstractDistanceBasedAlgorithm
          Provides an abstract algorithm already setting the distance function.
AbstractDistanceBasedAlgorithm.Parameterizer
          Parameterization helper class.
Algorithm
           Specifies the requirements for any algorithm that is to be executable by the main class.
 

Classes in de.lmu.ifi.dbs.elki.algorithm used by de.lmu.ifi.dbs.elki.algorithm.outlier.trivial
AbstractAlgorithm
           This class serves also as a model of implementing an algorithm within this framework.
Algorithm
           Specifies the requirements for any algorithm that is to be executable by the main class.
 

Classes in de.lmu.ifi.dbs.elki.algorithm used by de.lmu.ifi.dbs.elki.algorithm.statistics
AbstractAlgorithm
           This class serves also as a model of implementing an algorithm within this framework.
AbstractDistanceBasedAlgorithm
          Provides an abstract algorithm already setting the distance function.
AbstractDistanceBasedAlgorithm.Parameterizer
          Parameterization helper class.
Algorithm
           Specifies the requirements for any algorithm that is to be executable by the main class.
 

Classes in de.lmu.ifi.dbs.elki.algorithm used by de.lmu.ifi.dbs.elki.workflow
Algorithm
           Specifies the requirements for any algorithm that is to be executable by the main class.
 


Release 0.4.0 (2011-09-20_1324)