Open-source machine learning: R meets Weka

被引:259
作者
Hornik, Kurt [1 ]
Buchta, Christian [2 ]
Zeileis, Achim [1 ]
机构
[1] Vienna Univ Econ & Business Adm, Dept Math & Stat, A-1090 Vienna, Austria
[2] Vienna Univ Econ & Business Adm, Inst Tourism & Leisure Studies, A-1090 Vienna, Austria
关键词
Association Rule; Business Intelligence; Tree Learner; Interface Function; Interface Class;
D O I
10.1007/s00180-008-0119-7
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
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.
引用
收藏
页码:225 / 232
页数:8
相关论文
共 12 条
[1]  
[Anonymous], 2007, R LANG ENV STAT COMP
[2]  
CAREY V, 2007, ARJI ANOTHER R JAVA
[3]  
Chambers J.M., 1991, Statistical Models in S, DOI 10.1002/sim.4780110717
[4]  
Ellson J, 2004, MATH VIS, P127
[5]  
GENTRY J, 2007, RGRAPHVIZ PLOTTING C
[6]  
Hahsler M, 2005, J STAT SOFTW, V14
[7]  
Hornik K., 2007, RWeka: An R interface to Weka
[8]   Unbiased recursive partitioning: A conditional inference framework [J].
Hothorn, Torsten ;
Hornik, Kurt ;
Zeileis, Achim .
JOURNAL OF COMPUTATIONAL AND GRAPHICAL STATISTICS, 2006, 15 (03) :651-674
[9]  
LANG DT, 2005, SJAVA OMEGAHAT INTER
[10]  
SCHAUERHUBER M, 2007, DATA ANAL MACHINE LE