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Iterator-based algorithms in self-tuning discovery of partial implications

Author
Balcazar, J. L.; García-Sáiz, D.; de la Dehesa, J.
Type of activity
Presentation of work at congresses
Name of edition
10th International Conference on Formal Concept Analysis
Date of publication
2012
Presentation's date
2012-05-07
Book of congress proceedings
Formal Concept Analysis 2012: contributions to the 10th International Conference on Formal Concept Analysis (ICFCA 2012): Leuven, Belgium, May 6-10, 2012
First page
14
Last page
28
Publisher
CEUR Workshop Proceedings
Repository
http://hdl.handle.net/2117/20269 Open in new window
URL
http://ceur-ws.org/Vol-876/paper2.pdf Open in new window
Abstract
We describe the internal algorithmics of our recent implementation of a closure-based self-tuning associator: yacaree. This system is designed so as not to request the user to specify any threshold. In order to avoid the need of a support threshold, we introduce an algorithm that constructs closed sets in order of decreasing support; we are not aware of any similar previous algorithm. In order not to overwhelm the user with large quantities of partial implications, our system filters the output...
Citation
Balcazar, J.; García-Sáiz, D.; de la Dehesa, J. Iterator-based algorithms in self-tuning discovery of partial implications. A: International Conference on Formal Concept Analysis. "Formal Concept Analysis 2012: contributions to the 10th International Conference on Formal Concept Analysis (ICFCA 2012): Leuven, Belgium, May 6-10, 2012". Leuven: CEUR Workshop Proceedings, 2012, p. 14-28.
Keywords
Association mining, Iterators, Parameter-free mining, Python
Group of research
LARCA - Laboratory of Relational Algorithmics, Complexity and Learnability

Participants

  • Balcazar Navarro, Jose Luis  (author and speaker )
  • García Sáiz, Diego  (author and speaker )
  • de la Dehesa, Javier  (author and speaker )

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