Uses of Package
de.lmu.ifi.dbs.elki.data.model

Packages that use de.lmu.ifi.dbs.elki.data.model

Package	Description
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.affinitypropagation	Affinity Propagation (AP) clustering.
de.lmu.ifi.dbs.elki.algorithm.clustering.biclustering	Biclustering algorithms
de.lmu.ifi.dbs.elki.algorithm.clustering.correlation	Correlation clustering algorithms
de.lmu.ifi.dbs.elki.algorithm.clustering.em	Expectation-Maximization clustering algorithm.
de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan	Generalized DBSCAN Generalized DBSCAN is an abstraction of the original DBSCAN idea, that allows the use of arbitrary "neighborhood" and "core point" predicates.
de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.parallel	Parallel versions of Generalized DBSCAN.
de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.birch	BIRCH clustering.
de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.extraction	Extraction of partitional clusterings from hierarchical results.
de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans	K-means clustering and variations
de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.initialization	Initialization strategies for k-means.
de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.parallel	Parallelized implementations of k-means.
de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.quality	Quality measures for k-Means results.
de.lmu.ifi.dbs.elki.algorithm.clustering.meta	Meta clustering algorithms, that get their result from other clusterings or external sources.
de.lmu.ifi.dbs.elki.algorithm.clustering.onedimensional	Clustering algorithms for one-dimensional data.
de.lmu.ifi.dbs.elki.algorithm.clustering.optics	OPTICS family of 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.clustering.uncertain	Clustering algorithms for uncertain data.
de.lmu.ifi.dbs.elki.algorithm.outlier.clustering	Clustering based outlier detection.
de.lmu.ifi.dbs.elki.algorithm.outlier.subspace	Subspace outlier detection methods Methods that detect outliers in subspaces (projections) of the data set.
de.lmu.ifi.dbs.elki.algorithm.outlier.trivial	Trivial outlier detection algorithms: no outliers, all outliers, label outliers.
de.lmu.ifi.dbs.elki.data	Basic classes for different data types, database object types and label types
de.lmu.ifi.dbs.elki.data.model	Cluster models classes for various algorithms
de.lmu.ifi.dbs.elki.data.synthetic.bymodel	Generator using a distribution model specified in an XML configuration file GeneratorXMLSpec is a standalone application that loads an XML specification file and generates a synthetic data set according to the specifications given.
de.lmu.ifi.dbs.elki.datasource.parser	Parsers for different file formats and data types The general use-case for any parser is to create objects out of an InputStream (e.g. by reading a data file).
de.lmu.ifi.dbs.elki.evaluation.clustering	Evaluation of clustering results
de.lmu.ifi.dbs.elki.evaluation.outlier	Evaluate an outlier score using a misclassification based cost model
de.lmu.ifi.dbs.elki.result	Result types, representation and handling
de.lmu.ifi.dbs.elki.result.textwriter	Text serialization (CSV, Gnuplot, Console, ...)
de.lmu.ifi.dbs.elki.visualization	Visualization package of ELKI
de.lmu.ifi.dbs.elki.visualization.opticsplot	Code for drawing OPTICS plots
de.lmu.ifi.dbs.elki.visualization.visualizers.optics	Visualizers that do work on OPTICS plots
de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.cluster	Visualizers for clustering results based on 2D projections
de.lmu.ifi.dbs.elki.visualization.visualizers.visunproj	Visualizers that do not use a particular projection
tutorial.clustering	Classes from the tutorial on implementing a custom k-means variation

Classes in de.lmu.ifi.dbs.elki.data.model used by de.lmu.ifi.dbs.elki.algorithm

Class and Description
CorrelationAnalysisSolution A solution of correlation analysis is a matrix of equations describing the dependencies.

Classes in de.lmu.ifi.dbs.elki.data.model used by de.lmu.ifi.dbs.elki.algorithm.clustering

Class and Description
MeanModel Cluster model that stores a mean for the cluster.
Model Base interface for Model classes.
PrototypeModel Cluster model that stores a prototype for each cluster.

Classes in de.lmu.ifi.dbs.elki.data.model used by de.lmu.ifi.dbs.elki.algorithm.clustering.affinitypropagation

Class and Description
MedoidModel Cluster model that stores a mean for the cluster.

Classes in de.lmu.ifi.dbs.elki.data.model used by de.lmu.ifi.dbs.elki.algorithm.clustering.biclustering

Class and Description
BiclusterModel Wrapper class to provide the basic properties of a Bicluster.
BiclusterWithInversionsModel This code was factored out of the Bicluster class, since not all biclusters have inverted rows.

Classes in de.lmu.ifi.dbs.elki.data.model used by de.lmu.ifi.dbs.elki.algorithm.clustering.correlation

Class and Description
CorrelationModel Cluster model using a filtered PCA result and an centroid.
DimensionModel Cluster model additionally providing a cluster dimensionality.
Model Base interface for Model classes.

Classes in de.lmu.ifi.dbs.elki.data.model used by de.lmu.ifi.dbs.elki.algorithm.clustering.em

Class and Description
EMModel Cluster model of an EM cluster, providing a mean and a full covariance Matrix.
MeanModel Cluster model that stores a mean for the cluster.

Classes in de.lmu.ifi.dbs.elki.data.model used by de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan

Class and Description
Model Base interface for Model classes.

Classes in de.lmu.ifi.dbs.elki.data.model used by de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.parallel

Class and Description
Model Base interface for Model classes.

Classes in de.lmu.ifi.dbs.elki.data.model used by de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.birch

Class and Description
MeanModel Cluster model that stores a mean for the cluster.

Classes in de.lmu.ifi.dbs.elki.data.model used by de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.extraction

Class and Description
DendrogramModel Model for dendrograms, provides the height of this subtree.
Model Base interface for Model classes.

Classes in de.lmu.ifi.dbs.elki.data.model used by de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans

Class and Description
KMeansModel Trivial subclass of the MeanModel that indicates the clustering to be produced by k-means (so the Voronoi cell visualization is sensible).
MeanModel Cluster model that stores a mean for the cluster.
MedoidModel Cluster model that stores a mean for the cluster.
Model Base interface for Model classes.

Classes in de.lmu.ifi.dbs.elki.data.model used by de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.initialization

Class and Description
MeanModel Cluster model that stores a mean for the cluster.

Classes in de.lmu.ifi.dbs.elki.data.model used by de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.parallel

Class and Description
KMeansModel Trivial subclass of the MeanModel that indicates the clustering to be produced by k-means (so the Voronoi cell visualization is sensible).

Classes in de.lmu.ifi.dbs.elki.data.model used by de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.quality

Class and Description
MeanModel Cluster model that stores a mean for the cluster.

Classes in de.lmu.ifi.dbs.elki.data.model used by de.lmu.ifi.dbs.elki.algorithm.clustering.meta

Class and Description
Model Base interface for Model classes.

Classes in de.lmu.ifi.dbs.elki.data.model used by de.lmu.ifi.dbs.elki.algorithm.clustering.onedimensional

Class and Description
ClusterModel Generic cluster model.

Classes in de.lmu.ifi.dbs.elki.data.model used by de.lmu.ifi.dbs.elki.algorithm.clustering.optics

Class and Description
OPTICSModel Model for an OPTICS cluster

Classes in de.lmu.ifi.dbs.elki.data.model used by de.lmu.ifi.dbs.elki.algorithm.clustering.subspace

Class and Description
Model Base interface for Model classes.
SubspaceModel Model for Subspace Clusters.

Classes in de.lmu.ifi.dbs.elki.data.model used by de.lmu.ifi.dbs.elki.algorithm.clustering.trivial

Class and Description
Model Base interface for Model classes.

Classes in de.lmu.ifi.dbs.elki.data.model used by de.lmu.ifi.dbs.elki.algorithm.clustering.uncertain

Class and Description
KMeansModel Trivial subclass of the MeanModel that indicates the clustering to be produced by k-means (so the Voronoi cell visualization is sensible).

Classes in de.lmu.ifi.dbs.elki.data.model used by de.lmu.ifi.dbs.elki.algorithm.outlier.clustering

Class and Description
MeanModel Cluster model that stores a mean for the cluster.

Classes in de.lmu.ifi.dbs.elki.data.model used by de.lmu.ifi.dbs.elki.algorithm.outlier.subspace

Class and Description
SubspaceModel Model for Subspace Clusters.

Classes in de.lmu.ifi.dbs.elki.data.model used by de.lmu.ifi.dbs.elki.algorithm.outlier.trivial

Class and Description
Model Base interface for Model classes.

Classes in de.lmu.ifi.dbs.elki.data.model used by de.lmu.ifi.dbs.elki.data

Class and Description
Model Base interface for Model classes.

Classes in de.lmu.ifi.dbs.elki.data.model used by de.lmu.ifi.dbs.elki.data.model

Class and Description
BiclusterModel Wrapper class to provide the basic properties of a Bicluster.
ClusterModel Generic cluster model.
DendrogramModel Model for dendrograms, provides the height of this subtree.
MeanModel Cluster model that stores a mean for the cluster.
Model Base interface for Model classes.
PrototypeModel Cluster model that stores a prototype for each cluster.
SimplePrototypeModel Cluster model that stores a prototype for each cluster.

Classes in de.lmu.ifi.dbs.elki.data.model used by de.lmu.ifi.dbs.elki.data.synthetic.bymodel

Class and Description
Model Base interface for Model classes.

Classes in de.lmu.ifi.dbs.elki.data.model used by de.lmu.ifi.dbs.elki.datasource.parser

Class and Description
Model Base interface for Model classes.

Classes in de.lmu.ifi.dbs.elki.data.model used by de.lmu.ifi.dbs.elki.evaluation.clustering

Class and Description
Model Base interface for Model classes.

Classes in de.lmu.ifi.dbs.elki.data.model used by de.lmu.ifi.dbs.elki.evaluation.outlier

Class and Description
Model Base interface for Model classes.

Classes in de.lmu.ifi.dbs.elki.data.model used by de.lmu.ifi.dbs.elki.result

Class and Description
Model Base interface for Model classes.

Classes in de.lmu.ifi.dbs.elki.data.model used by de.lmu.ifi.dbs.elki.result.textwriter

Class and Description
Model Base interface for Model classes.

Classes in de.lmu.ifi.dbs.elki.data.model used by de.lmu.ifi.dbs.elki.visualization

Class and Description
Model Base interface for Model classes.

Classes in de.lmu.ifi.dbs.elki.data.model used by de.lmu.ifi.dbs.elki.visualization.opticsplot

Class and Description
Model Base interface for Model classes.

Classes in de.lmu.ifi.dbs.elki.data.model used by de.lmu.ifi.dbs.elki.visualization.visualizers.optics

Class and Description
OPTICSModel Model for an OPTICS cluster

Classes in de.lmu.ifi.dbs.elki.data.model used by de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.cluster

Class and Description
Model Base interface for Model classes.

Classes in de.lmu.ifi.dbs.elki.data.model used by de.lmu.ifi.dbs.elki.visualization.visualizers.visunproj

Class and Description
Model Base interface for Model classes.

Classes in de.lmu.ifi.dbs.elki.data.model used by tutorial.clustering

Class and Description
MeanModel Cluster model that stores a mean for the cluster.