Mining a New Fault-Tolerant Pattern Type as an Alternative to Formal Concept Discovery-Reference-Cited by-同舟云学术

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Mining a New Fault-Tolerant Pattern Type as an Alternative to Formal Concept Discovery

Published:2006 Issue: Volume: Page:144-157
ISSN:0302-9743
Container-title:Conceptual Structures: Inspiration and Application
language:
Short-container-title:

Author:

Besson Jérémy,Robardet Céline,Boulicaut Jean-François

Publisher

Springer Berlin Heidelberg

Link

http://link.springer.com/content/pdf/10.1007/11787181_11

Reference18 articles.

1. Lecture Notes in Computer Science;J. Besson,2005

2. Besson, J., Robardet, C., Boulicaut, J.-F., Rome, S.: Constraint-based bi-set mining for biologically relevant pattern discovery in microarray data. IDA journal 9(1), 59–82 (2005)

3. Blake, C., Merz, C.: UCI repository of machine learning databases (1998)

4. Bucila, C., Gehrke, J.E., Kifer, D., White, W.: Dualminer: A dual-pruning algorithm for itemsets with constraints. In: ACM SIGKDD, pp. 42–51 (2002)

5. François, P., Robert, C., Cremilleux, B., Bucharles, C., Demongeot, J.: Variables processing in expert system building: application to the aetiological diagnosis of infantile meningitis. Med. Inf. 15(2), 115–124 (1990)

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