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  • Fuzzy association analysis extracts relationships from data. The result of fuzzy association analysis depends on a chosen t-norm that is used for calculating confidence and support measures of mined association rules. We show that the set of mined association rules might change depending on the t-norm. We measure the distances of sets of mined rules with different t-norms and also with set of rules mined by crisp association analysis. We experiment with various datasets and partitioning methods to examine relationships of mined rules by different t-norms. Our experiments shed new light on application of fuzzy association mining and confirm that fuzzy association analysis usually brings signifficantly different results when compared to results given by crisp (non-fuzzy) association analysis.
  • Fuzzy association analysis extracts relationships from data. The result of fuzzy association analysis depends on a chosen t-norm that is used for calculating confidence and support measures of mined association rules. We show that the set of mined association rules might change depending on the t-norm. We measure the distances of sets of mined rules with different t-norms and also with set of rules mined by crisp association analysis. We experiment with various datasets and partitioning methods to examine relationships of mined rules by different t-norms. Our experiments shed new light on application of fuzzy association mining and confirm that fuzzy association analysis usually brings signifficantly different results when compared to results given by crisp (non-fuzzy) association analysis. (en)
Title
  • The Role of a T-norm and Partitioning in Fuzzy Association Analysis
  • The Role of a T-norm and Partitioning in Fuzzy Association Analysis (en)
skos:prefLabel
  • The Role of a T-norm and Partitioning in Fuzzy Association Analysis
  • The Role of a T-norm and Partitioning in Fuzzy Association Analysis (en)
skos:notation
  • RIV/61988987:17610/14:A1501B7C!RIV15-MSM-17610___
http://linked.open...avai/riv/aktivita
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  • P(ED1.1.00/02.0070), S
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  • 43074
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  • RIV/61988987:17610/14:A1501B7C
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  • fuzzy association analysis; t-norm; association rules (en)
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  • [526C627435F8]
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  • Varšava
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  • Strengthening Links between Data Analysis and Soft Computing
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  • Kupka, Jiří
  • Rusnok, Pavel
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number of pages
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  • Springer-Verlag
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  • 978-3-319-10764-6
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  • 17610
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