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Scalable Estimates of Concept Stability

Aleksey Buzmakov 1, 2 Sergei O. Kuznetsov 2 Amedeo Napoli 1 
1 ORPAILLEUR - Knowledge representation, reasonning
Inria Nancy - Grand Est, LORIA - NLPKD - Department of Natural Language Processing & Knowledge Discovery
Abstract : Data mining aims at finding interesting patterns from datasets, where ``interesting'' means reflecting intrinsic dependencies in the domain of interest rather than just in the dataset. Concept stability is a popular relevancy measure in FCA. Experimental results of this paper show that high stability of a concept for a context derived from the general population suggests that concepts with the same intent in other samples drawn from the population have also high stability. A new estimate of stability is introduced and studied. It is experimentally shown that the introduced estimate gives a better approximation than the Monte Carlo approach introduced earlier.
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Submitted on : Tuesday, December 16, 2014 - 2:49:23 PM
Last modification on : Thursday, August 4, 2022 - 5:18:44 PM
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Aleksey Buzmakov, Sergei O. Kuznetsov, Amedeo Napoli. Scalable Estimates of Concept Stability. 12th International Conference on Formal Concept Analysis (ICFCA 2014), 2014, Cluj-Napoca, Romania. pp.157 - 172, ⟨10.1007/978-3-319-07248-7_12⟩. ⟨hal-01095920⟩



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