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Contingency Matrix Theory II: Degree of Dependence as Granularity

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Języki publikacji
EN
Abstrakty
EN
The degree of granularity of a contingency table is closely related with that of dependence of contingency tables. We investigate these relations from the viewpoints of determinantal devisors and determinants. From the results of determinantal divisors, it seems that the devisors provide information on the degree of dependencies between the matrix of the whole elements and its submatrices and the increase of the degree of granularity may lead to that of dependence. However, the other approach shows that a constraint on the sample size of a contingency table is very strong, which leads to the evaluation formula where the increase of degree of granularity gives the decrease of dependency
Słowa kluczowe
Wydawca
Rocznik
Strony
427--442
Opis fizyczny
bibliogr. 8 poz., tab.
Twórcy
autor
autor
  • Department of Medical Informatics, Shimane University, School of Medicine, Enya-cho Izumo City, Shimane 693-8501 Japan, tsumoto@computer.org
Bibliografia
  • [1] Butz, C.: Exploiting contextual independencies in web search and user profiling, Proceedings of World Congress on Computational Intelligence (WCCI'2002) (CD-ROM), 2002.
  • [2] Pawlak, Z.: Rough Sets, Kluwer Academic Publishers, Dordrecht, 1991.
  • [3] Skowron, A., Grzymala-Busse, J.: From rough set theory to evidence theory, in: Advances in the Dempster-Shafer Theory of Evidence (R. Yager, M. Fedrizzi, J. Kacprzyk, Eds.), John Wiley & Sons, New York, 1994, 193-236.
  • [4] Tsumoto, S.: Automated Induction of Medical Expert System Rules from Clinical Databases based on Rough Set Theory, Information Sciences, 112, 1998, 67-84.
  • [5] Tsumoto, S.: Knowledge discovery in clinical databases and evaluation of discovered knowledge in outpatient clinic, Information Sciences, 124, 2000, 125-137.
  • [6] Tsumoto, S.: Statistical Independence as Linear Independence, Electronic Notes in Theoretical Computer Science (A. Skowron,M. Szczuka, Eds.), 82, Elsevier, 2003.
  • [7] Tsumoto, S., Hirano, S.: Contingency Matrix Theory, Information Sciences (submitted), 2008.
  • [8] Tsumoto, S., Tanaka, H.: Automated Discovery of Medical Expert System Rules from Clinical Databases based on Rough Sets, Proceedings of the Second International Conference on Knowledge Discovery and Data Mining 96, AAAI Press, Palo Alto, 1996.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BUS8-0004-0027
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