Project Summary
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.
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.
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.
In a Nutshell, ELKI...
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has a well established, mature codebase
maintained by a small development team
with decreasing Y-O-Y commits -
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took an estimated 56 years of effort (COCOMO model)
starting with its first commit in July, 2005
ending with its most recent commit 2 months ago
Quick Reference
GNU Affero General Public License v3.0 or later
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Include Copyright
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Include License
Include Install Instructions
These details are provided for information only. No information here is legal advice and should not be used as such.
Project Security
Vulnerabilities per Version ( last 10 releases )
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30 Day SummaryAug 8 2024 — Sep 7 2024
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