ELKI Data Mining Framework

ELKI LogoELKI 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.

Further information can be found on the ELKI homepage. The source code is available on github.

Publications

  • Erich Schubert, Alexander Koos, Tobias Emrich, Andreas Züfle, Klaus Arthur Schmid, and Arthur Zimek.
    A Framework for Clustering Uncertain Data.
    In: Proceedings of the VLDB Endowment 8 (12). 2015, 1976–1979
    [ELKI] [pdf] [DOI:10.14778/2824032.2824115] [bibtex]
  • Elke Achtert, Hans-Peter Kriegel, Erich Schubert, and Arthur Zimek.
    Interactive Data Mining with 3D-Parallel-Coordinate-Trees.
    In: Proceedings of the ACM International Conference on Management of Data (SIGMOD), New York City, NY. 2013, 1009–1012
    [ELKI] [DOI:10.1145/2463676.2463696] [bibtex]
  • Elke Achtert, Sascha Goldhofer, Hans-Peter Kriegel, Erich Schubert, and Arthur Zimek.
    Evaluation of Clusterings – Metrics and Visual Support.
    In: Proceedings of the 28th International Conference on Data Engineering (ICDE), Washington, DC. 2012, 1285–1288
    [ELKI] [DOI:10.1109/ICDE.2012.128] [bibtex]
  • Elke Achtert, Ahmed Hettab, Hans-Peter Kriegel, Erich Schubert, and Arthur Zimek.
    Spatial Outlier Detection: Data, Algorithms, Visualizations.
    In: Proceedings of the 12th International Symposium on Spatial and Temporal Databases (SSTD), Minneapolis, MN. 2011, 512–516, Best Demonstration Paper Award
    [ELKI] [DOI:10.1007/978-3-642-22922-0_41] [bibtex]
  • Elke Achtert, Hans-Peter Kriegel, Lisa Reichert, Erich Schubert, Remigius Wojdanowski, and Arthur Zimek.
    Visual Evaluation of Outlier Detection Models.
    In: Proceedings of the 15th International Conference on Database Systems for Advanced Applications (DASFAA), Tsukuba, Japan. 2010, 396–399
    [ELKI] [poster] [DOI:10.1007/978-3-642-12098-5_34] [bibtex]
  • Elke Achtert, Thomas Bernecker, Hans-Peter Kriegel, Erich Schubert, and Arthur Zimek.
    ELKI in Time: ELKI 0.2 for the Performance Evaluation of Distance Measures for Time Series.
    In: Proceedings of the 11th International Symposium on Spatial and Temporal Databases (SSTD), Aalborg, Denmark. 2009, 436–440
    [ELKI] [pdf] [poster] [DOI:10.1007/978-3-642-02982-0_35] [bibtex]
  • Elke Achtert, Hans-Peter Kriegel, and Arthur Zimek.
    ELKI: A Software System for Evaluation of Subspace Clustering Algorithms.
    In: 20th International Conference on Scientific and Statistical Database Management, SSDBM 2008, Hong Kong, China. 2008, 580–585
    [ELKI] [preprint (pdf)] [poster (pdf)] [DOI:10.1007/978-3-540-69497-7_41] [bibtex]