ELKI: A Software System for Evaluation of Subspace Clustering Algorithms
Source: University of Munich
In an active research area like data mining, a plethora of algorithms is proposed every year. Most of them, however, are presented once and never heard about again. On the other hand, newly proposed algorithms are often evaluated in a sloppy way taking into account only one or two partners for comparison of efficiency and effectiveness, presumably because for most algorithms no implementation is at hand. And if an implementation is provided by the authors, a fair comparison is nonetheless all but impossible due to different performance properties of different programming languages, frameworks, and, last but not least, implementation details.