ELKI

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

See:
Description

Packages

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.

How to make use of this framework

Development of new applications

Extension

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.

Usage

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.

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.