Science Score: 54.0%
This score indicates how likely this project is to be science-related based on various indicators:
-
✓CITATION.cff file
Found CITATION.cff file -
✓codemeta.json file
Found codemeta.json file -
✓.zenodo.json file
Found .zenodo.json file -
○DOI references
-
○Academic publication links
-
✓Committers with academic emails
6 of 60 committers (10.0%) from academic institutions -
○Institutional organization owner
-
○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (14.9%) to scientific vocabulary
Keywords
Repository
ELKI Data Mining Toolkit
Basic Info
- Host: GitHub
- Owner: elki-project
- License: agpl-3.0
- Language: Java
- Default Branch: main
- Homepage: https://elki-project.github.io/
- Size: 55.1 MB
Statistics
- Stars: 820
- Watchers: 54
- Forks: 325
- Open Issues: 4
- Releases: 0
Topics
Metadata Files
README.md
ELKI
Environment for Developing KDD-Applications Supported by Index-Structures
Quick Summary
ELKI is an open source (AGPLv3) data mining software written in Java. The focus of ELKI is research in algorithms, with an emphasis on unsupervised methods in cluster analysis and outlier detection. In order to achieve high performance and scalability, ELKI offers many data index structures such as the R*-tree that can provide major performance gains. ELKI is designed to be easy to extend for researchers and students in this domain, and welcomes contributions in particular of new methods. ELKI aims at providing a large collection of highly parameterizable algorithms, in order to allow easy and fair evaluation and benchmarking of algorithms.
Download
You can download precompiled ELKI releases from the home page, or you can use standard Java dependency management such as Gradle and Maven.
Gradle:
groovy
dependencies {
compile group: 'io.github.elki-project', name: 'elki', version:'0.8.0'
}
Maven:
xml
<!-- https://mvnrepository.com/artifact/io.github.elki-project/elki -->
<dependency>
<groupId>io.github.elki-project</groupId>
<artifactId>elki</artifactId>
<version>0.8.0</version>
</dependency>
Background
Data mining research leads to many algorithms for similar tasks. A fair and useful comparison of these algorithms is difficult due to several reasons: * Implementations of comparison partners are not at hand. * If implementations of different authors are provided, an evaluation in terms of efficiency is biased to evaluate the efforts of different authors in efficient programming instead of evaluating algorithmic merits.
On the other hand, efficient data management tools like index-structures can show considerable impact on data mining tasks and are therefore useful for a broad variety of algorithms.
In ELKI, data mining algorithms and data management tasks are separated and allow for an independent evaluation. This separation makes ELKI unique among data mining frameworks like Weka or Rapidminer and frameworks for index structures like GiST. At the same time, ELKI is open to arbitrary data types, distance or similarity measures, or file formats. The fundamental approach is the independence of file parsers or database connections, data types, distances, distance functions, and data mining algorithms. Helper classes, e.g. for algebraic or analytic computations are available for all algorithms on equal terms.
With the development and publication of ELKI, we humbly hope to serve the data mining and database research community beneficially. The framework is free for scientific usage ("free" as in "open source", see License for details). In case of application of ELKI in scientific publications, we would appreciate credit in form of a citation of the appropriate publication (see our list of publications), that is, the publication related to the release of ELKI you were using.
The people behind ELKI are documented on the Team page.
The ELKI wiki: Tutorials, HowTos, Documentation
Beginners may want to start at the HowTo documents, Examples and Tutorials to help with difficult configuration scenarios and beginning with ELKI development.
This website serves as community development hub and task tracker for both bug reports, Tutorials, FAQ, general issues and development tasks.
The most important documentation pages are: Tutorial, JavaDoc, FAQ, InputFormat, DataTypes, DistanceFunctions, DataSets, Development, Parameterization, Visualization, Benchmarking, and the list of Algorithms and RelatedPublications.
Getting ELKI: Download and Citation Policy
You can download ELKI including source code on the Releases page.
ELKI uses the AGPLv3 License, a well-known open source license.
There is a list of Publications that accompany the ELKI releases. When using ELKI in your scientific work, you should cite the publication corresponding to the ELKI release you are using, to give credit. This also helps to improve the repeatability of your experiments. We would also appreciate if you contributed your algorithm to ELKI to allow others to reproduce your results and compare with your algorithm (which in turn will likely get you citations). We try to document every publication used for implementing ELKI: the page RelatedPublications is generated from the source code annotations.
Efficiency Benchmarking with ELKI
ELKI is quite fast (see some of our benchmark results) but the focus lies on a broad coverage of algorithms and variations. We discourage cross-platform benchmarking, because it is easy to produce misleading results by comparing apples and oranges. For fair comparability, you should implement all algorithms within ELKI, and use the same APIs. We have also observed Java JDK versions have a large impact on the runtime performance. To make your results reproducible, please cite the version you have been using. See also Benchmarking.
Bug Reports and Contact
You can browse the open bug reports or create a new bug report.
We also appreciate any comments, suggestions and code contributions.
You can contact the core development team by e-mail: elki () dbs ifi lmu de
Design Goals
- Extensibility - ELKI has a very modular design. We want to allow arbitrary combinations of data types, distance functions, algorithms, input formats, index structures and evaluations methods
- Contributions - ELKI grows only as fast as people contribute. By having a modular design that allows small contributions such as single distance functions and single algorithms, we can have students and external contributors participate in the progress of ELKI
- Completeness - for an exhaustive comparison of methods, we aim at covering as much published and credited work as we can
- Fairness - It is easy to do an unfair comparison by badly implementing a competitor. We try to implement every method as good as we can, and by publishing the source code allow for external improvements. We try to add all proposed improvements, such as index structures for faster range and kNN queries
- Performance - the modular architecture of ELKI allows optimized versions of algorithms and index structures for acceleration
- Progress - ELKI is changing with every release. To accomodate new features and enhance performance, API breakages are unavoidable. We hope to get a stable API with the 1.0 release, but we are not there yet.
Building ELKI
ELKI is built using the Gradle wrapper:
./gradlew shadowJar
will produce a single executable jar file named elki-bundle-<VERSION>.jar.
Individual jar files can be built using:
./gradlew jar
A complete build (with tests and JavaDoc, it will take a few minutes) can be triggered as:
./gradlew build
Eclipse can build ELKI, and the easiest way is to use elki-bundle as classpath, which includes everything enabled.
Owner
- Name: ELKI
- Login: elki-project
- Kind: organization
- Location: Technische Universität Dortmund, Germany
- Website: https://elki-project.github.io/
- Repositories: 3
- Profile: https://github.com/elki-project
ELKI Data Mining Toolkit
Citation (CITATION.cff)
cff-version: 1.2.0
message: "If you use this software, please cite it as below."
authors:
- family-names: Schubert
given-names: Erich
orcid: 0000-0001-9143-4880
- family-names: Zimek
given-names: Arthur
orcid: 0000-0001-7713-4208
title: "ELKI Data Mining Framework"
version: 0.8.0
date-released: 2022-10-08
license: AGPL-3.0
preferred-citation:
title: "Automatic Indexing for Similarity Search in ELKI"
doi: "10.1007/978-3-031-17849-8_16"
year: "2022"
type: conference-paper
conference: "Similarity Search and Applications - 15th International Conference, SISAP 2022, Bologna, Italy, October 5-7, 2022, Proceedings"
authors:
- family-names: Schubert
given-names: Erich
references:
- title: "ELKI: A Software System for Evaluation of Subspace Clustering Algorithms"
doi: "10.1007/978-3-540-69497-7_41"
year: "2008"
type: conference-paper
conference: "Scientific and Statistical Database Management, 20th International Conference, SSDBM 2008, Hong Kong, China, July 9-11, 2008, Proceedings"
authors:
- family-names: Achtert
given-names: Elke
- family-names: Kriegel
given-names: Hans-Peter
- family-names: Zimek
given-names: Arthur
- title: "ELKI in Time: ELKI 0.2 for the Performance Evaluation of Distance Measures for Time Series"
doi: "10.1007/978-3-642-02982-0_35"
year: "2009"
type: conference-paper
conference: "Advances in Spatial and Temporal Databases, 11th International Symposium, SSTD 2009, Aalborg, Denmark, July 8-10, 2009, Proceedings"
authors:
- family-names: Achtert
given-names: Elke
- family-names: Bernecker
given-names: Thomas
- family-names: Kriegel
given-names: Hans-Peter
- family-names: Schubert
given-names: Erich
- family-names: Zimek
given-names: Arthur
- title: "Visual Evaluation of Outlier Detection Models"
doi: "10.1007/978-3-642-12098-5_34"
year: "2010"
type: conference-paper
conference: "Database Systems for Advanced Applications, 15th International Conference, DASFAA 2010, Tsukuba, Japan, April 1-4, 2010, Proceedings, Part II"
authors:
- family-names: Achtert
given-names: Elke
- family-names: Kriegel
given-names: Hans-Peter
- family-names: Reichert
given-names: Lisa
- family-names: Schubert
given-names: Erich
- family-names: Wojdanowski
given-names: Remigius
- family-names: Zimek
given-names: Arthur
- title: "Spatial Outlier Detection: Data, Algorithms, Visualizations"
doi: "10.1007/978-3-642-22922-0_41"
year: "2011"
type: conference-paper
conference: "Advances in Spatial and Temporal Databases - 12th International Symposium, SSTD 2011, Minneapolis, MN, USA, August 24-26, 2011, Proceedings"
authors:
- family-names: Achtert
given-names: Elke
- family-names: Hettab
given-names: Ahmed
- family-names: Kriegel
given-names: Hans-Peter
- family-names: Schubert
given-names: Erich
- family-names: Zimek
given-names: Arthur
- title: "Evaluation of Clusterings - Metrics and Visual Support"
doi: "10.1109/ICDE.2012.128"
year: "2012"
type: conference-paper
conference: "IEEE 28th International Conference on Data Engineering (ICDE 2012), Washington, DC, USA (Arlington, Virginia), 1-5 April, 2012"
authors:
- family-names: Achtert
given-names: Elke
- family-names: Goldhofer
given-names: Sascha
- family-names: Kriegel
given-names: Hans-Peter
- family-names: Schubert
given-names: Erich
- family-names: Zimek
given-names: Arthur
- title: "Interactive data mining with 3D-parallel-coordinate-trees"
doi: "10.1145/2463676.2463696"
year: "2013"
type: conference-paper
conference: "Proceedings of the ACM SIGMOD International Conference on Management of Data, SIGMOD 2013, New York, NY, USA, June 22-27, 2013"
authors:
- family-names: Achtert
given-names: Elke
- family-names: Kriegel
given-names: Hans-Peter
- family-names: Schubert
given-names: Erich
- family-names: Zimek
given-names: Arthur
- title: "ELKI: A large open-source library for data analysis - ELKI Release 0.7.5 \"Heidelberg\""
year: "2019"
type: article
journal: "CoRR"
authors:
- family-names: Schubert
given-names: Erich
- family-names: Zimek
given-names: Arthur
- title: "A Framework for Clustering Uncertain Data"
doi: "10.14778/2824032.2824115"
year: "2015"
type: article
journal: "Proc. VLDB Endow."
authors:
- family-names: Schubert
given-names: Erich
- family-names: Koos
given-names: Alexander
- family-names: Emrich
given-names: Tobias
- family-names: Züfle
given-names: Andreas
- family-names: Schmid
given-names: Klaus Arthur
- family-names: Zimek
given-names: Arthur
- title: "Automatic Indexing for Similarity Search in ELKI"
doi: "10.1007/978-3-031-17849-8_16"
year: "2022"
type: conference-paper
conference: "Similarity Search and Applications - 15th International Conference, SISAP 2022, Bologna, Italy, October 5-7, 2022, Proceedings"
authors:
- family-names: Schubert
given-names: Erich
GitHub Events
Total
- Issues event: 1
- Watch event: 32
- Issue comment event: 2
- Push event: 1
- Fork event: 4
- Create event: 1
Last Year
- Issues event: 1
- Watch event: 32
- Issue comment event: 2
- Push event: 1
- Fork event: 4
- Create event: 1
Committers
Last synced: 7 months ago
Top Committers
| Name | Commits | |
|---|---|---|
| Erich Schubert | s****e@d****e | 7,086 |
| Elke Achtert | a****t@d****e | 1,481 |
| Arthur Zimek | z****k@d****e | 896 |
| Stefanie Wanka | w****a@d****e | 126 |
| Ahmed Hettab | h****b@c****e | 93 |
| Remigius Wojdanowski | w****i@c****e | 86 |
| ARandomTree | r****e@u****u | 76 |
| Lisa Reichert | r****t@d****e | 64 |
| Heidi Kolb | k****h@c****e | 58 |
| Andreas Lang | a****g@t****e | 53 |
| Florian Frankenberger | f****b@c****e | 52 |
| Merlin Dietrich | e****n@p****t | 48 |
| Stefan Baier | b****t@c****e | 37 |
| Jonathan von Bruenken | m****o@c****e | 31 |
| Matthew Arcifa | d****1 | 28 |
| Alexander Koos | k****a@d****e | 28 |
| Robert Roedler | r****r@c****e | 27 |
| kirner | k****r@c****e | 24 |
| Niklas Strahmann0 | n****n@u****u | 19 |
| Jonas | S****s@g****m | 17 |
| Sascha Goldhofer | g****a@c****e | 15 |
| Florian Nuecke | n****e@c****e | 14 |
| Tibor Goldschwendt | g****t@c****e | 11 |
| Sebastian Rühl | s****l@g****m | 10 |
| Julian Erhard | j****d@c****e | 10 |
| Peter Kunath | k****h@d****e | 8 |
| Dominik | D****r@w****e | 8 |
| Peer Kröger | k****r@d****e | 7 |
| Sebastian Hollizeck | h****k@c****e | 7 |
| Simon Mittermüller | e****i@d****e | 7 |
| and 30 more... | ||
Committer Domains (Top 20 + Academic)
Issues and Pull Requests
Last synced: 4 months ago
All Time
- Total issues: 57
- Total pull requests: 47
- Average time to close issues: about 1 month
- Average time to close pull requests: about 2 months
- Total issue authors: 46
- Total pull request authors: 20
- Average comments per issue: 3.05
- Average comments per pull request: 2.34
- Merged pull requests: 2
- Bot issues: 0
- Bot pull requests: 0
Past Year
- Issues: 1
- Pull requests: 0
- Average time to close issues: N/A
- Average time to close pull requests: N/A
- Issue authors: 1
- Pull request authors: 0
- Average comments per issue: 0.0
- Average comments per pull request: 0
- Merged pull requests: 0
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
- neilireson (5)
- bastian-wur (4)
- kno10 (3)
- johnnybostar (2)
- frewenta (2)
- dkajtoch (2)
- StatguyUser (1)
- sven-h (1)
- moemode (1)
- rainfalj (1)
- jcfj (1)
- jneelampalli (1)
- foolnotion (1)
- Syntax-Sorcerer87 (1)
- mmisiewicz-yext (1)
Pull Request Authors
- BraulioSanchez (10)
- faisal-hameed (7)
- patrickkostjens (6)
- commandini (3)
- ARandomTree (3)
- flexkra (2)
- ghost (2)
- andiwg (2)
- alanmazankiewicz (2)
- SIDSSIDS (1)
- pokemonxue (1)
- fredps (1)
- paulk-asert (1)
- AbhishekSharma102 (1)
- lapplislazuli (1)
Top Labels
Issue Labels
Pull Request Labels
Packages
- Total packages: 38
- Total downloads: unknown
- Total docker downloads: 452
-
Total dependent packages: 61
(may contain duplicates) -
Total dependent repositories: 35
(may contain duplicates) - Total versions: 47
repo1.maven.org: de.lmu.ifi.dbs.elki:elki
ELKI - Main Module – Open-Source Data-Mining Framework with Index Acceleration
- Homepage: https://elki-project.github.io/
- Documentation: https://appdoc.app/artifact/de.lmu.ifi.dbs.elki/elki/
- License: GNU Affero General Public License (AGPL) version 3.0
-
Latest release: 0.7.5
published almost 7 years ago
Rankings
repo1.maven.org: de.lmu.ifi.dbs.elki:elki-clustering
ELKI - Clustering Algorithms – Open-Source Data-Mining Framework with Index Acceleration
- Homepage: https://elki-project.github.io/
- Documentation: https://appdoc.app/artifact/de.lmu.ifi.dbs.elki/elki-clustering/
- License: GNU Affero General Public License (AGPL) version 3.0
-
Latest release: 0.7.5
published almost 7 years ago
Rankings
repo1.maven.org: de.lmu.ifi.dbs.elki:elki-core-util
ELKI - Core Utilities – Open-Source Data-Mining Framework with Index Acceleration
- Homepage: https://elki-project.github.io/
- Documentation: https://appdoc.app/artifact/de.lmu.ifi.dbs.elki/elki-core-util/
- License: GNU Affero General Public License (AGPL) version 3.0
-
Latest release: 0.7.5
published almost 7 years ago
Rankings
repo1.maven.org: de.lmu.ifi.dbs.elki:elki-batik-visualization
ELKI - Batik Visualization – Open-Source Data-Mining Framework with Index Acceleration
- Homepage: https://elki-project.github.io/
- Documentation: https://appdoc.app/artifact/de.lmu.ifi.dbs.elki/elki-batik-visualization/
- License: GNU Affero General Public License (AGPL) version 3.0
-
Latest release: 0.7.5
published almost 7 years ago
Rankings
repo1.maven.org: de.lmu.ifi.dbs.elki:elki-index
ELKI - Index Core – Open-Source Data-Mining Framework with Index Acceleration
- Homepage: https://elki-project.github.io/
- Documentation: https://appdoc.app/artifact/de.lmu.ifi.dbs.elki/elki-index/
- License: GNU Affero General Public License (AGPL) version 3.0
-
Latest release: 0.7.5
published almost 7 years ago
Rankings
repo1.maven.org: de.lmu.ifi.dbs.elki:elki-core-dbids-int
ELKI - Core DBIDs Integer Implementation – Open-Source Data-Mining Framework with Index Acceleration
- Homepage: https://elki-project.github.io/
- Documentation: https://appdoc.app/artifact/de.lmu.ifi.dbs.elki/elki-core-dbids-int/
- License: GNU Affero General Public License (AGPL) version 3.0
-
Latest release: 0.7.5
published almost 7 years ago
Rankings
repo1.maven.org: de.lmu.ifi.dbs.elki:elki-core-math
ELKI - Core Mathematics and Statistics – Open-Source Data-Mining Framework with Index Acceleration
- Homepage: https://elki-project.github.io/
- Documentation: https://appdoc.app/artifact/de.lmu.ifi.dbs.elki/elki-core-math/
- License: GNU Affero General Public License (AGPL) version 3.0
-
Latest release: 0.7.5
published almost 7 years ago
Rankings
repo1.maven.org: de.lmu.ifi.dbs.elki:elki-core
ELKI - Core Miscellaneous – Open-Source Data-Mining Framework with Index Acceleration
- Homepage: https://elki-project.github.io/
- Documentation: https://appdoc.app/artifact/de.lmu.ifi.dbs.elki/elki-core/
- License: GNU Affero General Public License (AGPL) version 3.0
-
Latest release: 0.7.5
published almost 7 years ago
Rankings
repo1.maven.org: de.lmu.ifi.dbs.elki:elki-index-preprocessed
ELKI - Indexes based on preprocessing – Open-Source Data-Mining Framework with Index Acceleration
- Homepage: https://elki-project.github.io/
- Documentation: https://appdoc.app/artifact/de.lmu.ifi.dbs.elki/elki-index-preprocessed/
- License: GNU Affero General Public License (AGPL) version 3.0
-
Latest release: 0.7.5
published almost 7 years ago
Rankings
repo1.maven.org: de.lmu.ifi.dbs.elki:elki-outlier
ELKI - Outlier Detection Algorithms – Open-Source Data-Mining Framework with Index Acceleration
- Homepage: https://elki-project.github.io/
- Documentation: https://appdoc.app/artifact/de.lmu.ifi.dbs.elki/elki-outlier/
- License: GNU Affero General Public License (AGPL) version 3.0
-
Latest release: 0.7.5
published almost 7 years ago
Rankings
repo1.maven.org: de.lmu.ifi.dbs.elki:elki-core-dbids
ELKI - Core DBIDs API – Open-Source Data-Mining Framework with Index Acceleration
- Homepage: https://elki-project.github.io/
- Documentation: https://appdoc.app/artifact/de.lmu.ifi.dbs.elki/elki-core-dbids/
- License: GNU Affero General Public License (AGPL) version 3.0
-
Latest release: 0.7.5
published almost 7 years ago
Rankings
repo1.maven.org: de.lmu.ifi.dbs.elki:elki-core-api
ELKI - Core APIs – Open-Source Data-Mining Framework with Index Acceleration
- Homepage: https://elki-project.github.io/
- Documentation: https://appdoc.app/artifact/de.lmu.ifi.dbs.elki/elki-core-api/
- License: GNU Affero General Public License (AGPL) version 3.0
-
Latest release: 0.7.5
published almost 7 years ago
Rankings
repo1.maven.org: de.lmu.ifi.dbs.elki:elki-persistent
ELKI - Persistence Layer – Open-Source Data-Mining Framework with Index Acceleration
- Homepage: https://elki-project.github.io/
- Documentation: https://appdoc.app/artifact/de.lmu.ifi.dbs.elki/elki-persistent/
- License: GNU Affero General Public License (AGPL) version 3.0
-
Latest release: 0.7.5
published almost 7 years ago
Rankings
repo1.maven.org: de.lmu.ifi.dbs.elki:elki-database
ELKI - Database – Open-Source Data-Mining Framework with Index Acceleration
- Homepage: https://elki-project.github.io/
- Documentation: https://appdoc.app/artifact/de.lmu.ifi.dbs.elki/elki-database/
- License: GNU Affero General Public License (AGPL) version 3.0
-
Latest release: 0.7.5
published almost 7 years ago
Rankings
repo1.maven.org: de.lmu.ifi.dbs.elki:elki-logging
ELKI - Logging – Open-Source Data-Mining Framework with Index Acceleration
- Homepage: https://elki-project.github.io/
- Documentation: https://appdoc.app/artifact/de.lmu.ifi.dbs.elki/elki-logging/
- License: GNU Affero General Public License (AGPL) version 3.0
-
Latest release: 0.7.5
published almost 7 years ago
Rankings
repo1.maven.org: de.lmu.ifi.dbs.elki:elki-uncertain
ELKI - Uncertain data handling – Open-Source Data-Mining Framework with Index Acceleration
- Homepage: https://elki-project.github.io/
- Documentation: https://appdoc.app/artifact/de.lmu.ifi.dbs.elki/elki-uncertain/
- License: GNU Affero General Public License (AGPL) version 3.0
-
Latest release: 0.7.5
published almost 7 years ago
Rankings
repo1.maven.org: de.lmu.ifi.dbs.elki:elki-gui-minigui
ELKI - MiniGUI Command Line Builder – Open-Source Data-Mining Framework with Index Acceleration
- Homepage: https://elki-project.github.io/
- Documentation: https://appdoc.app/artifact/de.lmu.ifi.dbs.elki/elki-gui-minigui/
- License: GNU Affero General Public License (AGPL) version 3.0
-
Latest release: 0.7.5
published almost 7 years ago
Rankings
repo1.maven.org: de.lmu.ifi.dbs.elki:elki-index-mtree
ELKI - M-Tree Variants – Open-Source Data-Mining Framework with Index Acceleration
- Homepage: https://elki-project.github.io/
- Documentation: https://appdoc.app/artifact/de.lmu.ifi.dbs.elki/elki-index-mtree/
- License: GNU Affero General Public License (AGPL) version 3.0
-
Latest release: 0.7.5
published almost 7 years ago
Rankings
repo1.maven.org: de.lmu.ifi.dbs.elki:elki-data-generator
ELKI - Data Generator – Open-Source Data-Mining Framework with Index Acceleration
- Homepage: https://elki-project.github.io/
- Documentation: https://appdoc.app/artifact/de.lmu.ifi.dbs.elki/elki-data-generator/
- License: GNU Affero General Public License (AGPL) version 3.0
-
Latest release: 0.7.5
published almost 7 years ago
Rankings
repo1.maven.org: de.lmu.ifi.dbs.elki:elki-input
ELKI - Data Input – Open-Source Data-Mining Framework with Index Acceleration
- Homepage: https://elki-project.github.io/
- Documentation: https://appdoc.app/artifact/de.lmu.ifi.dbs.elki/elki-input/
- License: GNU Affero General Public License (AGPL) version 3.0
-
Latest release: 0.7.5
published almost 7 years ago
Rankings
repo1.maven.org: de.lmu.ifi.dbs.elki:elki-timeseries
ELKI - Time Series – Open-Source Data-Mining Framework with Index Acceleration
- Homepage: https://elki-project.github.io/
- Documentation: https://appdoc.app/artifact/de.lmu.ifi.dbs.elki/elki-timeseries/
- License: GNU Affero General Public License (AGPL) version 3.0
-
Latest release: 0.7.5
published almost 7 years ago
Rankings
repo1.maven.org: de.lmu.ifi.dbs.elki:elki-precomputed
ELKI - External Distances – Open-Source Data-Mining Framework with Index Acceleration
- Homepage: https://elki-project.github.io/
- Documentation: https://appdoc.app/artifact/de.lmu.ifi.dbs.elki/elki-precomputed/
- License: GNU Affero General Public License (AGPL) version 3.0
-
Latest release: 0.7.5
published almost 7 years ago
Rankings
repo1.maven.org: de.lmu.ifi.dbs.elki:elki-core-parallel
ELKI - Parallel Processing Core – Open-Source Data-Mining Framework with Index Acceleration
- Homepage: https://elki-project.github.io/
- Documentation: https://appdoc.app/artifact/de.lmu.ifi.dbs.elki/elki-core-parallel/
- License: GNU Affero General Public License (AGPL) version 3.0
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Latest release: 0.7.5
published almost 7 years ago
Rankings
repo1.maven.org: de.lmu.ifi.dbs.elki:elki-classification
ELKI - Classification Algorithms – Open-Source Data-Mining Framework with Index Acceleration
- Homepage: https://elki-project.github.io/
- Documentation: https://appdoc.app/artifact/de.lmu.ifi.dbs.elki/elki-classification/
- License: GNU Affero General Public License (AGPL) version 3.0
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Latest release: 0.7.5
published almost 7 years ago
Rankings
repo1.maven.org: de.lmu.ifi.dbs.elki:elki-itemsets
ELKI - Itemset Mining – Open-Source Data-Mining Framework with Index Acceleration
- Homepage: https://elki-project.github.io/
- Documentation: https://appdoc.app/artifact/de.lmu.ifi.dbs.elki/elki-itemsets/
- License: GNU Affero General Public License (AGPL) version 3.0
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Latest release: 0.7.5
published almost 7 years ago
Rankings
repo1.maven.org: de.lmu.ifi.dbs.elki:elki-index-rtree
ELKI - R-Tree Variants – Open-Source Data-Mining Framework with Index Acceleration
- Homepage: https://elki-project.github.io/
- Documentation: https://appdoc.app/artifact/de.lmu.ifi.dbs.elki/elki-index-rtree/
- License: GNU Affero General Public License (AGPL) version 3.0
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Latest release: 0.7.5
published almost 7 years ago
Rankings
repo1.maven.org: de.lmu.ifi.dbs.elki:elki-index-lsh
ELKI - Locality Sensitive Hashing – Open-Source Data-Mining Framework with Index Acceleration
- Homepage: https://elki-project.github.io/
- Documentation: https://appdoc.app/artifact/de.lmu.ifi.dbs.elki/elki-index-lsh/
- License: GNU Affero General Public License (AGPL) version 3.0
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Latest release: 0.7.5
published almost 7 years ago
Rankings
repo1.maven.org: de.lmu.ifi.dbs.elki:elki-core-distance
ELKI - Core Distance Functions – Open-Source Data-Mining Framework with Index Acceleration
- Homepage: https://elki-project.github.io/
- Documentation: https://appdoc.app/artifact/de.lmu.ifi.dbs.elki/elki-core-distance/
- License: GNU Affero General Public License (AGPL) version 3.0
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Latest release: 0.7.5
published almost 7 years ago
Rankings
repo1.maven.org: de.lmu.ifi.dbs.elki:elki-geo
ELKI - Geography Module – Open-Source Data-Mining Framework with Index Acceleration
- Homepage: https://elki-project.github.io/
- Documentation: https://appdoc.app/artifact/de.lmu.ifi.dbs.elki/elki-geo/
- License: GNU Affero General Public License (AGPL) version 3.0
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Latest release: 0.7.5
published almost 7 years ago
Rankings
repo1.maven.org: de.lmu.ifi.dbs.elki:elki-core-data
ELKI - Core Data Types – Open-Source Data-Mining Framework with Index Acceleration
- Homepage: https://elki-project.github.io/
- Documentation: https://appdoc.app/artifact/de.lmu.ifi.dbs.elki/elki-core-data/
- License: GNU Affero General Public License (AGPL) version 3.0
-
Latest release: 0.7.5
published almost 7 years ago
Rankings
repo1.maven.org: de.lmu.ifi.dbs.elki:elki-index-various
ELKI - Various indexes – Open-Source Data-Mining Framework with Index Acceleration
- Homepage: https://elki-project.github.io/
- Documentation: https://appdoc.app/artifact/de.lmu.ifi.dbs.elki/elki-index-various/
- License: GNU Affero General Public License (AGPL) version 3.0
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Latest release: 0.7.5
published almost 7 years ago
Rankings
repo1.maven.org: de.lmu.ifi.dbs.elki:elki-libsvm
ELKI - LibSVM based extensions – Open-Source Data-Mining Framework with Index Acceleration
- Homepage: https://elki-project.github.io/
- Documentation: https://appdoc.app/artifact/de.lmu.ifi.dbs.elki/elki-libsvm/
- License: GNU Affero General Public License (AGPL) version 3.0
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Latest release: 0.7.5
published almost 7 years ago
Rankings
repo1.maven.org: de.lmu.ifi.dbs.elki:elki-bundle
ELKI is an open source (AGPLv3) data mining software written in Java. The focus of ELKI is research in algorithms, with an emphasis on unsupervised methods in cluster analysis and outlier detection. In order to achieve high performance and scalability, ELKI offers many data index structures such as the R*-tree that can provide major performance gains. ELKI is designed to be easy to extend for researchers and students in this domain, and welcomes contributions in particular of new methods. ELKI aims at providing a large collection of highly parameterizable algorithms, in order to allow easy and fair evaluation and benchmarking of algorithms.
- Homepage: http://elki.dbs.ifi.lmu.de/
- Documentation: https://appdoc.app/artifact/de.lmu.ifi.dbs.elki/elki-bundle/
- License: GNU Affero General Public License (AGPL) version 3.0
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Latest release: 0.7.1
published almost 10 years ago
Rankings
repo1.maven.org: de.lmu.ifi.dbs.elki:elki-docutil
ELKI - Documentation Utilities – Open-Source Data-Mining Framework with Index Acceleration
- Homepage: https://elki-project.github.io/
- Documentation: https://appdoc.app/artifact/de.lmu.ifi.dbs.elki/elki-docutil/
- License: GNU Affero General Public License (AGPL) version 3.0
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Latest release: 0.7.5
published almost 7 years ago
Rankings
repo1.maven.org: de.lmu.ifi.dbs.elki:elki-tutorial
ELKI - Tutorial Algorithms – Open-Source Data-Mining Framework with Index Acceleration
- Homepage: https://elki-project.github.io/
- Documentation: https://appdoc.app/artifact/de.lmu.ifi.dbs.elki/elki-tutorial/
- License: GNU Affero General Public License (AGPL) version 3.0
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Latest release: 0.7.5
published almost 7 years ago
Rankings
repo1.maven.org: de.lmu.ifi.dbs.elki:elki-3dpc
ELKI - 3D Parallel Coordinate Trees Visualization – Open-Source Data-Mining Framework with Index Acceleration
- Homepage: https://elki-project.github.io/
- Documentation: https://appdoc.app/artifact/de.lmu.ifi.dbs.elki/elki-3dpc/
- License: GNU Affero General Public License (AGPL) version 3.0
-
Latest release: 0.7.5
published almost 7 years ago
Rankings
repo1.maven.org: de.lmu.ifi.dbs.elki:elki-project
ELKI is an open source (AGPLv3) data mining software written in Java. The focus of ELKI is research in algorithms, with an emphasis on unsupervised methods in cluster analysis and outlier detection. In order to achieve high performance and scalability, ELKI offers many data index structures such as the R*-tree that can provide major performance gains. ELKI is designed to be easy to extend for researchers and students in this domain, and welcomes contributions in particular of new methods. ELKI aims at providing a large collection of highly parameterizable algorithms, in order to allow easy and fair evaluation and benchmarking of algorithms.
- Homepage: http://elki.dbs.ifi.lmu.de/
- Documentation: https://appdoc.app/artifact/de.lmu.ifi.dbs.elki/elki-project/
- License: GNU Affero General Public License (AGPL) version 3.0
-
Latest release: 0.7.1
published almost 10 years ago
Rankings
repo1.maven.org: de.lmu.ifi.dbs.elki:elki-test-core
ELKI - Unit Test Core – Open-Source Data-Mining Framework with Index Acceleration
- Homepage: https://elki-project.github.io/
- Documentation: https://appdoc.app/artifact/de.lmu.ifi.dbs.elki/elki-test-core/
- License: GNU Affero General Public License (AGPL) version 3.0
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Latest release: 0.7.5
published almost 7 years ago
Rankings
Dependencies
- actions/checkout v2 composite
- actions/setup-java v1 composite
- codecov/codecov-action v1 composite
- actions/checkout v2 composite
- actions/setup-java v1 composite
- github/codeql-action/analyze v2 composite
- github/codeql-action/init v2 composite
- actions/checkout v2 composite
- actions/setup-java v1 composite