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Four-Fold Table Calculi for Discovery Science

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Discovey Science (DS 1998)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1532))

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Abstract

The goal of KDD is to search for interesting and useful patterns in data. Some of these patterns concern relations of two Boolean attributes ϕ and ψ. Such relations are evaluated on the basis of a four-fold table (FFT for short) 〈a, b, c, d〉 of ϕ and ψ. Here a is the number of objects satisfying both ϕ and ψ, b is the number of objects satisfying ϕ and not satisfying ψ, c is the number of objects not satisfying. and satisfying ψ and d is the number of objects not satisfying neither ϕ nor ψ. An example of such pattern is an association rule [1]. Four-Fold Table Predicate Calculi (FFTPC for short)will be introduced. Formulae of FFTPC correspond to patterns evaluated on the basis of FFT. FFTPC are defined and studied in connection with development of GUHA procedures, see e.g. [2,3,4]

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References

  1. Aggraval, R. et al: Fast Discovery of Association Rules. in Fayyad, U. M. et al.: Advances in Knowledge Discovery and Data Mining. AAAI Press, 1996.

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  2. Hajek, P., Holena, M.: Formal logics of discovery and hypothesis formation by machine. Accepted for “Discovery Science 1998”.

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  3. Rauch, J.: Logical foundations of mechanizing hypothesis formation from databases. Thesis, Mathematical institute of Czechoslovak Academy of Sciences Prague, 1986, 133 p. (in Czech)

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  4. Rauch, J.: Classes of Four-Fold Table Quantifiers. Accepted for “Principles of Data Mining and Knowledge Discovery 1998”

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© 1998 Springer-Verlag Berlin Heidelberg

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Rauch, J. (1998). Four-Fold Table Calculi for Discovery Science. In: Arikawa, S., Motoda, H. (eds) Discovey Science. DS 1998. Lecture Notes in Computer Science(), vol 1532. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-49292-5_43

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  • DOI: https://doi.org/10.1007/3-540-49292-5_43

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-65390-5

  • Online ISBN: 978-3-540-49292-4

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