Mining Fault-Tolerant Item Sets Using Subset Size Occurrence Distributions

Author:

Borgelt Christian,Kötter Tobias

Publisher

Springer Berlin Heidelberg

Reference20 articles.

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2. Agrawal, R., Srikant, R.: Fast Algorithms for Mining Association Rules. In: Proc. 20th Int. Conf. on Very Large Databases (VLDB 1994), Santiago de Chile, pp. 487–499. Morgan Kaufmann, San Mateo (1994)

3. Besson, J., Robardet, C., Boulicaut, J.-F.: Mining a New Fault-Tolerant Pattern Type as an Alternative to Formal Concept Discovery. In: Proc. Int. Conference on Computational Science (ICCS 2006), Reading, United Kingdom, pp. 144–157. Springer, Berlin (2006)

4. Berger, D., Borgelt, C., Diesmann, M., Gerstein, G., Grün, S.: An Accretion based Data Mining Algorithm for Identification of Sets of Correlated Neurons. In: 18th Ann. Computational Neuroscience Meeting (CNS*2009), Berlin, Germany (2009)

5. Borgelt, C., Wang, X.: SaM: A Split and Merge Algorithm for Fuzzy Frequent Item Set Mining. In: Proc. 13th Int. Fuzzy Systems Association World Congress and 6th Conf. of the European Society for Fuzzy Logic and Technology (IFSA/EUSFLAT 2009), Lisbon, Portugal, pp. 968–973. IFSA/EUSFLAT Organization Committee, Lisbon (2009)

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