A service provided by the WU Library and the WU IT-Services

Open-Source Machine Learning: R Meets Weka

Hornik, Kurt and Buchta, Christian and Zeileis, Achim (2007) Open-Source Machine Learning: R Meets Weka. Research Report Series / Department of Statistics and Mathematics, 50. Department of Statistics and Mathematics, WU Vienna University of Economics and Business, Vienna.

[img]
Preview
PDF
Download (222Kb) | Preview

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.

Item Type: Paper
Keywords: machine learning / statistical learning / Weka / R / Java / interface
Divisions: Departments > Finance, Accounting and Statistics > Statistics and Mathematics
Depositing User: Repository Administrator
Date Deposited: 14 Mar 2007 21:19
Last Modified: 27 Feb 2017 18:38
FIDES Link: https://bach.wu.ac.at/d/research/results/37836/
URI: http://epub.wu.ac.at/id/eprint/1188

Actions

View Item