High accuracy method for discovering quantitave association rules in datatables and databases
A. Shragai. Tel Aviv University
D.E. Tamir. Texas State University
M. Schneider. Natanya College
A. Kandel. University of South Florida
- Fuzzy Economic Review: Volume XIV, Number 1. May 2009
- DOI: 10.25102/fer.2009.01.01
This paper introduces a new and novel deterministic technique for mining association rules from quantitative data tables and databases and show how to use these techniques to devise a fuzzy-inference based apriori algorithm for discovering associations. The algorithm is sound and efficient. It introduces a complexity level that is equivalent…
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