OpenSubspace: An Open Source Framework for Evaluation and Exploration of Subspace Clustering Algorithms in WEKA

Research output: Contribution to book/anthology/report/proceedingArticle in proceedingsResearchpeer-review

  • Emmanuel Müller, RWTH Aachen University, Germany
  • Ira Assent
  • Stephan Günnemann, RWTH Aachen University, Germany
  • Thomas Seidl, RWTH Aachen University, Germany
Subspace clustering and projected clustering are recent research areas for clustering in high dimensional spaces. As the field is rather young, there is a lack of comparative studies on the advantages and disadvantages of the different algorithms. Part of the underlying problem is the lack of available open source implementations that could be used by researchers to understand, compare, and extend subspace and projected clustering algorithms. In this paper, we discuss the requirements for open source evaluation software. We propose OpenSubspace, an open source framework that meets these requirements. OpenSubspace integrates state-of-the-art performance measures and visualization techniques to foster research in subspace and projected clustering.
Original languageEnglish
Title of host publicationProceedings of OSDM 2009
Publication year2009
Pages1-12
Publication statusPublished - 2009
Externally publishedYes

See relations at Aarhus University Citationformats

ID: 47659962