Environment for
Supported by Index-Structures


ELKI: Environment for DeveLoping KDD-Applications Supported by Index-Structures.


de.lmu.ifi.dbs.elki ELKI framework "Environment for Developing KDD-Applications Supported by Index-Structures" KDDTask is the main class of the ELKI-Framework for command-line interaction.
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.correlation.cash Helper classes for the CASH algorithm.
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.subspace.clique Helper classes for the CLIQUE algorithm.
de.lmu.ifi.dbs.elki.algorithm.outlier Outlier detection algorithms
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.application Base classes for stand alone applications.
de.lmu.ifi.dbs.elki.application.cache Utility applications for the persistence layer such as distance cache builders.
de.lmu.ifi.dbs.elki.application.internal Internal utilities for development.
de.lmu.ifi.dbs.elki.application.visualization Visualization applications in ELKI.
de.lmu.ifi.dbs.elki.data Basic classes for different data types, database object types and label types.
de.lmu.ifi.dbs.elki.data.cluster Cluster classes.
de.lmu.ifi.dbs.elki.data.cluster.naming Naming schemes for clusters (for output when an algorithm doesn't generate cluster names).
de.lmu.ifi.dbs.elki.data.model Cluster models classes for various algorithms.
de.lmu.ifi.dbs.elki.data.synthetic Generators for synthetic data sets
de.lmu.ifi.dbs.elki.data.synthetic.bymodel Generator using a distribution model specified in an XML configuration file.
de.lmu.ifi.dbs.elki.data.synthetic.bymodel.distribution Data generators used by the model-based generator.
de.lmu.ifi.dbs.elki.database ELKI database layer - loading, storing, indexing and accessing data
de.lmu.ifi.dbs.elki.database.connection Database connections are classes implementing data sources.
de.lmu.ifi.dbs.elki.distance Distances and (in subpackages) distance functions and similarity functions.
de.lmu.ifi.dbs.elki.distance.distancefunction Distance functions for use within ELKI.
de.lmu.ifi.dbs.elki.distance.distancefunction.adapter Distance functions deriving distances from e.g. similarity measures
de.lmu.ifi.dbs.elki.distance.distancefunction.correlation Distance functions using correlations.
de.lmu.ifi.dbs.elki.distance.distancefunction.external Distance functions using external data sources.
de.lmu.ifi.dbs.elki.distance.distancefunction.subspace Distance functions based on subspaces.
de.lmu.ifi.dbs.elki.distance.distancefunction.timeseries Distance functions designed for time series.
de.lmu.ifi.dbs.elki.distance.similarityfunction Similarity functions.
de.lmu.ifi.dbs.elki.distance.similarityfunction.kernel Kernel functions.
de.lmu.ifi.dbs.elki.evaluation Functionality for the evaluation of algorithms.
de.lmu.ifi.dbs.elki.evaluation.paircounting Evaluation of clustering results via pair counting.
de.lmu.ifi.dbs.elki.evaluation.paircounting.generator Pair generation for pair counting evaluation.
de.lmu.ifi.dbs.elki.evaluation.roc Evaluation of rankings using ROC AUC (Receiver Operation Characteristics - Area Under Curve)
de.lmu.ifi.dbs.elki.index Index structure implementations
de.lmu.ifi.dbs.elki.index.tree Tree-based index structures
de.lmu.ifi.dbs.elki.index.tree.metrical Tree-based index structures for metrical vector spaces.
de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants M-Tree and variants.
de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees Metrical index structures based on the concepts of the M-Tree supporting processing of reverse k nearest neighbor queries by using the k-nn distances of the entries.
de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkapp MkAppTree
de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkcop MkCoPTree
de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkmax MkMaxTree
de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mktab MkTabTree
de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mtree MTree
de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.split Splitting strategies of nodes in an M-Tree (and variants).
de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.util Helper classes for the the M-Tree and it's variants.
de.lmu.ifi.dbs.elki.index.tree.spatial Tree-based index structures for spatial indexing.
de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants R*-Tree and variants.
de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.deliclu DeLiCluTree
de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.rdknn RdKNNTree
de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.rstar RStarTree
de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.util Utilities for R*-Tree and variants.
de.lmu.ifi.dbs.elki.logging Logging facility for controlling logging behavior of the complete framework.
de.lmu.ifi.dbs.elki.math Mathematical operations and utilities used throughout the framework.
de.lmu.ifi.dbs.elki.math.linearalgebra Linear Algebra package provides classes and computational methods for operations on matrices.
de.lmu.ifi.dbs.elki.math.linearalgebra.fitting Function to numerically fit a function (such as a Gaussian distribution to given data.
de.lmu.ifi.dbs.elki.math.linearalgebra.pca Principal Component Analysis (PCA) and Eigenvector processing.
de.lmu.ifi.dbs.elki.math.linearalgebra.pca.weightfunctions Weight functions used in weighted PCA via WeightedCovarianceMatrixBuilder
de.lmu.ifi.dbs.elki.math.spacefillingcurves Space filling curves.
de.lmu.ifi.dbs.elki.math.statistics Statistical tests and methods.
de.lmu.ifi.dbs.elki.normalization Data normalization (and reconstitution) of data sets.
de.lmu.ifi.dbs.elki.parser Parsers for different file formats and data types.
de.lmu.ifi.dbs.elki.parser.meta MetaParsers for different file formats and data types.
de.lmu.ifi.dbs.elki.persistent Persistent data management.
de.lmu.ifi.dbs.elki.preprocessing Preprocessors used for data preparation in a first step of various algorithms or distance and similarity measures.
de.lmu.ifi.dbs.elki.properties Property handling and main ELKI properties file.
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.result.textwriter.writers Serialization handlers for individual data types.
de.lmu.ifi.dbs.elki.utilities Utility and helper classes - commonly used data structures, output formatting, exceptions, ...
de.lmu.ifi.dbs.elki.utilities.heap Variants of heap structures.
de.lmu.ifi.dbs.elki.utilities.optionhandling Parameter handling and option descriptions.
de.lmu.ifi.dbs.elki.utilities.optionhandling.constraints Constraints allow to restrict possible values for parameters.
de.lmu.ifi.dbs.elki.utilities.output Helper-classes for output formatting.
de.lmu.ifi.dbs.elki.utilities.pairs Pairs and triples utility classes.
de.lmu.ifi.dbs.elki.utilities.progress Progress status objects (for UI)
de.lmu.ifi.dbs.elki.utilities.xml XML and XHTML utilities.
de.lmu.ifi.dbs.elki.visualization Visualization package of ELKI.
de.lmu.ifi.dbs.elki.visualization.batikutil Commonly used functionality useful for Apache Batik.
de.lmu.ifi.dbs.elki.visualization.colors Color scheme handling for ELKI.
de.lmu.ifi.dbs.elki.visualization.css Managing CSS styles / classes.
de.lmu.ifi.dbs.elki.visualization.savedialog Save dialog for SVG plots.
de.lmu.ifi.dbs.elki.visualization.scales Scales handling for plotting.
de.lmu.ifi.dbs.elki.visualization.svg Base SVG functionality (generation, markers, thumbnails, export, ...).


ELKI: Environment for DeveLoping KDD-Applications Supported by Index-Structures.

ELKI is a generic framework for a broad range of KDD-applications and their development. For background, contact-information, and contributors see http://www.dbs.ifi.lmu.de/research/KDD/ELKI/.

This is the documentation for version 0.2, published as:
Elke Achtert, Thomas Bernecker, Hans-Peter Kriegel, Erich Schubert, Arthur Zimek:
ELKI in Time: ELKI 0.2 for the Performance Evaluation of Distance Measures for Time Series.
In Proc. 11th International Symposium on Spatial and Temporal Databases (SSTD 2009), Aalborg, Denmark, 2009.

Workflow - Where Do Which Objects Go?

The database connection manages reading of input files or databases and provides a Database-Object as a virtual database to the KDDTask. The KDDTask applies a specified algorithm on this database and collects the result from the algorithm. Finally, KDDTask hands on the obtained result to a ResultHandler. The default-handler is ResultWriter, writing the result to STDOUT or, if specified, into a file.

visualization of passing of objects

How to make use of this framework

Development of new applications


To provide new applications one is simply to implement the specified interfaces. There are interfaces for a broad range of targets of development. Compare the tree of interfaces to get an overview concerning the provided interfaces.


To use the KDD-Framework we recommend an executable .jar-file: elki.jar. You get a description of usage by calling java -jar elki.jar -h.

The KNNExplorer application is explained on its own page.

Parameters and Parameter-Passing

The core class is KDDTask for command line interaction. This class' main method manages the reading of parameters from the standard input and passes the parameters to the corresponding classes which, in turn, could have parameters that expect parameterization.

visualization of parameterization

The main class KDDTask requires specification of an Algorithm to use, and a DatabaseConnection to manage the input. It can get assigned a specialized ResultHandler. The default ResultHandler ResultWriter expects a filename where to deploy the output. However, by omitting specification of a filename for output, the results will be given to standard output, thus it may be piped directly to another application.

For more information on using files and available formats as data input see de.lmu.ifi.dbs.elki.parser.

Furthermore a normalization can be specified for the input. You can additionally require to restore the original values for the output.

Which input is to be provided in what way is to be defined via parameters specifically for a certain DatabaseConnection.

The need for other parameters may differ from implementation to implementation. However, you need not to specify input nor output if you are going to implement an algorithm.

An extensive list of parameters can be browsed sorted by class or sorted by option ID.

Some examples of completely parameterized calls for different algorithms are described at example calls.

Release 0.2 (2009-07-06_1820)