---
Categories:
- Development
- Education
- GTK
- Science
- ArtificialIntelligence
- ComputerScience
Description:
C: '<p>ELKI: "Environment for Developing KDD-Applications Supported by Index-Structures" is a development
framework for data mining algorithms written in Java. It includes a large variety of popular data
mining algorithms, distance functions and index structures.</p><p>Its focus is particularly on clustering
and outlier detection methods, in contrast to many other data mining toolkits that focus on classification.
Additionally, it includes support for index structures to improve algorithm performance such as R*-Tree
and M-Tree.</p><p>The modular architecture is meant to allow adding custom components such as distance
functions or algorithms, while being able to reuse the other parts for evaluation.</p><p>This package
contains the compiled ELKI version, and launcher scripts.</p>'
en_AU: '<p>ELKI: "Environment for Developing KDD-Applications Supported by Index- Structures" is a development
framework for data mining algorithms written in Java. It includes a large variety of popular data
mining algorithms, distance functions and index structures.</p><p>Its focus is particularly on clustering
and outlier detection methods, in contrast to many other data mining toolkits that focus on classification.
Additionally, it includes support for index structures to improve algorithm performance such as R*-Tree
and M-Tree.</p><p>The modular architecture is meant to allow adding custom components such as distance
functions or algorithms, while being able to reuse the other parts for evaluation.</p><p>This package
contains the compiled ELKI version, and launcher scripts.</p>'
en_CA: '<p>ELKI: "Environment for Developing KDD-Applications Supported by Index- Structures" is a development
framework for data mining algorithms written in Java. It includes a large variety of popular data
mining algorithms, distance functions and index structures.</p><p>Its focus is particularly on clustering
and outlier detection methods, in contrast to many other data mining toolkits that focus on classification.
Additionally, it includes support for index structures to improve algorithm performance such as R*-Tree
and M-Tree.</p><p>The modular architecture is meant to allow adding custom components such as distance
functions or algorithms, while being able to reuse the other parts for evaluation.</p><p>This package
contains the compiled ELKI version, and launcher scripts.</p>'
en_GB: '<p>ELKI: "Environment for Developing KDD-Applications Supported by Index- Structures" is a development
framework for data mining algorithms written in Java. It includes a large variety of popular data
mining algorithms, distance functions and index structures.</p><p>Its focus is particularly on clustering
and outlier detection methods, in contrast to many other data mining toolkits that focus on classification.
Additionally, it includes support for index structures to improve algorithm performance such as R*-Tree
and M-Tree.</p><p>The modular architecture is meant to allow adding custom components such as distance
functions or algorithms, while being able to reuse the other parts for evaluation.</p><p>This package
contains the compiled ELKI version, and launcher scripts.</p>'
fr: '<p>ELKI : « Environnement pour le Développement d''applications KDD prises en charge par les structures
d''Index » est un environnement applicatif de développement pour les algorithmes d''exploration de
données, écrit en Java. Il comprend une large gamme d''algorithmes célèbres d''exploration de données,
de fonctions de distance et de structures d''index.</p><p>L''accent est mis particulièrement sur les
méthodes de détection de regroupements et de valeurs aberrantes, contrairement à de nombreux autres
outils d''exploration de données qui se concentrent sur la classification. En outre, il prend en charge
les structures d''index pour améliorer les performances d''algorithmes tels que R *-Tree et M-Tree.</p><p>L''architecture
modulaire est conçue pour permettre l''ajout de composants personnalisés tels que les fonctions ou
algorithmes de distance, tout en étant capable de réutiliser les autres parties pour évaluation.</p><p>This
package contains the compiled ELKI version, and launcher scripts.</p>'
gl: '<p>ELKI: "Environment for Developing KDD-Applications Supported by Index- Structures" is a development
framework for data mining algorithms written in Java. It includes a large variety of popular data
mining algorithms, distance functions and index structures.</p><p>Its focus is particularly on clustering
and outlier detection methods, in contrast to many other data mining toolkits that focus on classification.
Additionally, it includes support for index structures to improve algorithm performance such as R*-Tree
and M-Tree.</p><p>The modular architecture is meant to allow adding custom components such as distance
functions or algorithms, while being able to reuse the other parts for evaluation.</p><p>This package
contains the compiled ELKI version, and launcher scripts.</p>'
ID: elki.desktop
Icon:
cached: elki_elki-icon.png
Name:
C: ELKI
Package: elki
Summary:
C: Data mining algorithm development framework
Type: desktop-app
