ELKI
Environment for DeveLoping KDD-Applications Supported by
Index-Structures (ELKI) is a data mining software framework developed
for use in research and teaching.
ELKI is a framework that provides algorithms for clustering,
managing database indexes and outlier detection.
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 YALE and
frameworks for index structures like GiST.
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.
ELKI 0.5.0 beta1
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Price
Free to download
Size
10.9MB
License
AGPLv3
Developer
Ludwig Maximillian University of Munich
Website
www.dbs.ifi.lmu.de
System Requirements
Java SE 6
Support
Sites:
Documentation,
Mailing
List
Selected
Reviews:
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Features include:
- Minimalistic graphical user interface for interactive
parameterization of ELKI
algorithms
- Data mining algorithms such as k-means variations, outlier
detection ensembles
- Visualize results:
- Outlier Scores
- Clustering results
- Histograms
- ROC Curves
- OPTICS plots
- Index MBRs
- Parallel coordinates
- Voronoi cells
- Alpha shapes
- Cluster differences
- Index structures (various R-tree splitting and bulk loading
strategies)
- Evaluation methods (various clustering similarity measures)
- Spatial outlier detection visualization on geographical data
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Last Updated Monday, April 09 2012 @ 04:42 AM EDT
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