ELKI Environment for developing KDD applications supported by index structures
Download

ELKI Ranking & Summary

ELKI Tags

research data mining KDD development data mining research data mining algorithm KDD

ELKI Description

Environment for developing KDD applications supported by index structures Data mining research leads to many algorithms for similar tasks. A fair and useful comparison of these algorithms is difficult due to several reasons:· Implementations of comparison partners are not at hand.· If implementations of different authors are provided, an evaluation in terms of efficiency is biased to evaluate the efforts of different authors in efficient programming instead of evaluating algorithmic merits.On the other hand, efficient data management tools like index-structures can show considerable impact on data mining tasks and are therefore useful for a broad variety of algorithms.In ELKI, data management tasks and data mining algorithms 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. 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 classes, e.g. for algebraic or analytic computations are available for all algorithms on equal terms. Requirements: · Java 6 or later What's New in This Release: · New release with a focus on outlier detection methods and visualization (see publication P3), along with some general refactoring that improves memory efficiency and performance and a minimalistic GUI for interactive parameterization of ELKI algorithms.

ELKI Related Software