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The ELKI framework is written in Java and built around a modular architecture. Most currently included algorithms belong to clustering, outlier detection and database indexes. A key concept of ELKI is to allow the combination of arbitrary algorithms, data types, distance functions and indexes and evaluate these combinations.
Category
Data Mining Software
Features
• Open source data mining software
• High performance and scalability
• Simple visualization window
• Data management tasks
• Standard Java API
License
Open Source
Price
Free
Pricing
Subscription
Free Trial
Available
Users Size
Small (<50 employees), Medium (50 to 1000 employees), Enterprise (>1001 employees)
• Open source data mining software
• High performance and scalability
• Simple visualization window
• Data management tasks
• Standard Java API
What are the benefits?
• JAVA data mining software
• Allows R code
• Data mining and data management are worked as separate tasks
• Free for scientific use
• Community of users contributing with algorithm to ELKI
PAT Rating™
Editor Rating
Aggregated User Rating
Rate Here
Ease of use
7.5
6.1
Features & Functionality
7.5
8.6
Advanced Features
7.5
8.4
Integration
7.5
8.5
Performance
7.5
8.1
Customer Support
7.5
8.5
Implementation
8.1
Renew & Recommend
8.2
Bottom Line
ELKI is modeled around a database core, which uses a vertical data layout that stores data in column groups (similar to column families in NoSQL databases).
7.5
Editor Rating
8.1
Aggregated User Rating
4 ratings
You have rated this
The ELKI framework is written in Java and built around a modular architecture. Most currently included algorithms belong to clustering, outlier detection and database indexes.
A key concept of ELKI is to allow the combination of arbitrary algorithms, data types, distance functions and indexes and evaluate these combinations. When developing new algorithms or index structures, the existing components can be reused and combined.
ELKI is modeled around a database core, which uses a vertical data layout that stores data in column groups (similar to column families in NoSQL databases). This database core provides nearest neighbor search, range/radius search, and distance query functionality with index acceleration for a wide range of dissimilarity measures.
Algorithms based on such queries (e.g. k-nearest-neighbor algorithm, local outlier factor and DBSCAN) can be implemented easily and benefit from the index acceleration. The database core also provides fast and memory efficient collections for object collections and associative structures such as nearest neighbor lists.
The visualization module uses SVG for scalable graphics output, and Apache Batik for rendering of the user interface as well as lossless export into PostScript and PDF for easy inclusion in scientific publications in LaTeX. Exported files can be edited with SVG editors such as Inkscape.
Separate tasks for data mining and data management
What is best?
Here, an important advantage of this software is the accomplishment of separate tasks for data mining and data management, which allows an optimization of the programming and algorithms for these two components.
Company size
Medium (50 to 1000)
User Role
Super User
User Industry
Education
Rating
Ease of use8.1
Features & Functionality8.3
ELKI data mining software is fully written in Java. It works by searching algorithms, especially in unsupervised methods of class analysis. Programming is based on R, which provides a tremendous amount of code and exceptional performance, but with the advantage of being easy to access for researchers and students of the area. The goal is to provide a large number of algorithms, highly parameterizable, and from here to implement what best applies to a given task.
Advanced Features8.4
Integration8.5
Performance8.1
Training 8.2
Customer Support8.5
Implementation8.1
Renew & Recommend8.2
ADDITIONAL INFORMATION The ELKI software also allows the analysis of arbitrary data, measures of distance or similarity, and accessibility to different database file formats. The team that actively develops ELKI can be found on the website of this software as well as its qualifications. A number of scientific publications on the software can still be consulted, and accompany the releases of different versions of ELKI. A code base is also available through the ELKI website, where a variety of already tested and widely optimized functions can be used.
Separate tasks for data mining and data management
Here, an important advantage of this software is the accomplishment of separate tasks for data mining and data management, which allows an optimization of the programming and algorithms for these two components.
Medium (50 to 1000)
Super User
Education
ELKI data mining software is fully written in Java. It works by searching algorithms, especially in unsupervised methods of class analysis. Programming is based on R, which provides a tremendous amount of code and exceptional performance, but with the advantage of being easy to access for researchers and students of the area. The goal is to provide a large number of algorithms, highly parameterizable, and from here to implement what best applies to a given task.
ADDITIONAL INFORMATION
The ELKI software also allows the analysis of arbitrary data, measures of distance or similarity, and accessibility to different database file formats. The team that actively develops ELKI can be found on the website of this software as well as its qualifications. A number of scientific publications on the software can still be consulted, and accompany the releases of different versions of ELKI. A code base is also available through the ELKI website, where a variety of already tested and widely optimized functions can be used.