OPUS Miner Algorithm for Filtered Top-k Association Discovery

Provides a simple R interface to the OPUS Miner algorithm (implemented in C++) for finding the top-k productive, non-redundant itemsets from transaction data. The OPUS Miner algorithm uses the OPUS search algorithm to efficiently discover the key associations in transaction data, in the form of self-sufficient itemsets, using either leverage or lift. See < http://i.giwebb.com/index.php/research/association-discovery/> for more information in relation to the OPUS Miner algorithm.


Reference manual

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0.1-1 by Christoph Bergmeir, 2 years ago

Browse source code at https://github.com/cran/opusminer

Authors: Geoffrey I Webb [aut, cph] (OPUS Miner algorithm and C++ implementation , http://i.giwebb.com/index.php/research/association-discovery/) , Christoph Bergmeir [ctb, cre] , Angus Dempster [ctb, cph] (R interface)

Documentation:   PDF Manual  

Task views: Machine Learning & Statistical Learning

GPL-3 license

Imports Rcpp, arules, Matrix, methods

Linking to Rcpp

See at CRAN