Open-Source Machine Learning: R Meets Weka

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 enviro...

Full description

Bibliographic Details
Main Authors: Hornik, Kurt, Buchta, Christian, Zeileis, Achim
Format: Others
Language:en
Published: Department of Statistics and Mathematics, WU Vienna University of Economics and Business 2007
Subjects:
Online Access:http://epub.wu.ac.at/1188/1/document.pdf
Description
Summary: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. === Series: Research Report Series / Department of Statistics and Mathematics