On benchmarking frequent itemset mining algorithms: from measurement to analysis

Authors:
Balázs Rácz;Ferenc Bodon;Lars Schmidt-Thieme
Affiliations:
Research Institute of the Hungarian Academy of Sciences, Budapest, Hungary;Budapest University of Technology and Economics, Budapest, Hungary;Albert-Ludwigs-Universität, Freiburg, Georges-Koehler-Allee, Freiburg, Germany
Venue:
Proceedings of the 1st international workshop on open source data mining: frequent pattern mining implementations
Year:
2005

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Abstract

We point out problems of current practices in comparing Frequent Itemset Mining Implementations, and suggest techniques that can help to avoid the conclusions of measurements being tainted by these problems.