Open-source machine learning: R meets Weka

被引:0
|
作者
Kurt Hornik
Christian Buchta
Achim Zeileis
机构
[1] Wirtschaftsuniversität Wien,Department of Statistics and Mathematics
[2] Wirtschaftsuniversität Wien,Institute for Tourism and Leisure Studies
来源
Computational Statistics | 2009年 / 24卷
关键词
Association Rule; Business Intelligence; Tree Learner; Interface Function; Interface Class;
D O I
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中图分类号
学科分类号
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:7
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