Elki-project.github.io Website Review

ELKI: ENVIRONMENT FOR DEVELOPING KDD-APPLICATIONS SUPPORTED BY INDEX-STRUCTURES. ELKI is an open source (AGPLv3) data mining software written in Ja*a. The focus of ELKI is research in algorithms, with an emphasis on 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. Data mining research leads to many algorithms for similar tasks. A fair and useful comparison of these algorithms is difficult due to evaluation in terms of efficiency is biased to evaluate the efforts of different authors in efficient programming instead of evaluating On the other hand, efficient data management tools like index-structures can show considerable impact on data mining tasks and 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 Rapidminer and frameworks for index structures like GiST. At the same time, ELKI is open to arbitrary data types, distance or similarity measures, or file formats. The fundamental approach is the independence of file parsers or database connections, data types, distances, distance functions, and data mining algorithms. Helper clas*es, e.g. for algebraic or an*lytic computations are available for all algorithms on equal terms. With the development and publication of ELKI, we humbly hope to serve the data mining and database research community beneficially. The with difficult configuration scenarios and beginning with ELKI development.     compile group: 'de.lmu.ifi.dbs.elki', name: 'elki', version:'0.7.5' } cite the publication corresponding to the ELKI release you are using, to give credit. This also helps to improve the repeatability of your experiments. We would also appreciate if you contributed your algorithm to ELKI to allow others to reproduce your results and