A computational environment for mining association rules and frequent item sets in R

Mining frequent itemsets and association rules is a popular and well researched approach to discovering interesting relationships between variables in large databases. The R package arules will provide a basic infrastructure for creating and manipulating input data sets and for analyzing the resulting itemsets and rules.

Further developments include:

• Clustering of rules and segmentation of transaction data (includes the visualization and proximity measures)
  
  
• Developments of new, statistical interest measures for association rules
  
  
• Development of generators for artificial data