Open-source machine learning: R meets Weka View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2009-05

AUTHORS

Kurt Hornik, Christian Buchta, Achim Zeileis

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. More... »

PAGES

225-232

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s00180-008-0119-7

DOI

http://dx.doi.org/10.1007/s00180-008-0119-7

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1010234645


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