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

Autor
Balcazar, J. L.; García-Sáiz, D.; de la Dehesa, J.
Tipus d'activitat
Presentació treball a congrés
Nom de l'edició
10th International Conference on Formal Concept Analysis
Any de l'edició
2012
Data de presentació
2012-05-07
Llibre d'actes
Formal Concept Analysis 2012: contributions to the 10th International Conference on Formal Concept Analysis (ICFCA 2012): Leuven, Belgium, May 6-10, 2012
Pàgina inicial
14
Pàgina final
28
Editor
CEUR Workshop Proceedings
Repositori
http://hdl.handle.net/2117/20269 Obrir en finestra nova
URL
http://ceur-ws.org/Vol-876/paper2.pdf Obrir en finestra nova
Resum
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...
Citació
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.
Paraules clau
Association mining, Iterators, Parameter-free mining, Python
Grup de recerca
LARCA - Laboratori d'Algorísmia Relacional, Complexitat i Aprenentatge

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