ELKI
ELKI is a data mining software written in Java, with focus on research in algorithms
Features
ELKI is Environment for Developing KDD(Knowledge Discovery in Databases, “ Data Mining”)-Applications Supported by Index-Structures.
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 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 of additional methods. ELKI aims at providing a large collection of highly parameterizable algorithms, in order to allow easy and fair evaluation and benchmarking of algorithms. - Official website
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. - Wikipedia
ELKI is an open source data mining software with the focus on cluster analysis and outlier detection. In contrast to most other tools, it has support for index structures. - Stack Overflow
System Requirements
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Developer
Erich Schubert (Heidelberg University), Arthur Zimek (University of Southern Denmark), Ludwig Maximilians (University of München), Other contributors
Written in
Java
Initial Release
10 July 2008
Repository
License
Multiple such as the Apache, BSD or public domain for v0.4, AGPL v3 for v0.4 onward
Categories
Alternatives
Data Mining
Massive Online Analysis (MOA)
OpenNN
Orange
scikit-learn
Weka
Yooreeka
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