TY - UNPB
T1 - Open-Source Machine Learning: R meets Weka
AU - Hornik, Kurt
AU - Buchta, Christian
AU - Zeileis, Achim
PY - 2007/4/1
Y1 - 2007/4/1
N2 - 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.
AB - 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.
U2 - 10.57938/034d368c-037d-4b44-9d82-3232cebad1df
DO - 10.57938/034d368c-037d-4b44-9d82-3232cebad1df
M3 - WU Working Paper
T3 - Research Report Series / Department of Statistics and Mathematics
BT - Open-Source Machine Learning: R meets Weka
CY - Wien
ER -