Open-Source Machine Learning: R meets Weka

Kurt Hornik, Christian Buchta, Achim Zeileis

Publication: Working/Discussion PaperWU Working Paper

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Abstract

Two of the prime open-source environments available for machine/statistical learning in data mining and knowledge discovery are the software packages Weka and R which have emerged from the machine learning and statistics communities, respectively. To make the different sets of tools from both environments available in a single unified system, an R package RWeka is suggested which interfaces Weka's functionality to R. With only a thin layer of (mostly R) code, a set of general interface generators is provided which can set up interface functions with the usual "R look and feel", re-using Weka's standardized interface of learner classes (including classifiers, clusterers, associators, filters, loaders, savers, and stemmers) with associated methods.
Original languageEnglish
Place of PublicationWien
Publication statusPublished - 1 Apr 2007

Publication series

NameResearch Report Series / Department of Statistics and Mathematics
No.50

WU Working Paper Series

  • Research Report Series / Department of Statistics and Mathematics

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