Abstract
In the paper infinite information systems are investigated which are used in pattern recognition,discrete optimization, computational geometry. The depth and the size of deterministic and nondeterministic decision trees over such information systems are studied. A partition of the set of all infinite information systems on two classes is considered. Systems from the first class are near to the best from the point of view of deterministic and nondeterministic decision tree time and space complexity. Decision trees for systems from the second class have in the worst case large time or space complexity. In proofs (which are too long and not included to the paper) methods of test theory [1,2] and rough set theory [8,9] are used.
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References
Chegis, I.A., Yablonskii, S.V.: Logical methods of electric circuit control. Trudy MIAN SSSR 51 (1958) 270–360 (in Russian)
Moshkov, M.Ju.: Conditional tests. Problemy Kybernetiki 40. Edited by S.V. Yablonskii. Nauka Publishers, Mosco w (1983) 131–170 (in Russian)
Moshkov, M.Ju.: Decision Trees. Theory and Applications. Nizhni Novgorod University Publishers, Nizhni Novgorod (1994) (in Russian)
Moshkov, M.Ju.: Comparative analysis of deterministic and nondeterministic decision tree complexity. Global approach. Fundamenta Informaticae 25(2) (1996) 201–214
Moshkov, M.Ju.: Unimprovable upper bounds on time complexity of decision trees. Fundamenta Informaticae 31(2) (1997) 157–184
Moshkov, M.Ju.: On time complexity of decision trees. Rough Sets in Knowledge Discovery 1. Methodology and Applications (Studies in Fuzziness and Soft Computing 18). Edited by L. Polkowski and A. Skowron. Phisica-Verlag. A Springer-Verlag Company (1998) 160–191
Moshkov, M.Ju.: Deterministic and nondeterministic decision trees for rough computing. Fundamenta Informaticae 41(3) (2000) 301–311
Pawlak, Z.: Rough Sets-Theoretical Aspects of Reasoning about Data. Kluwer Academic Publishers, Dordrecht, Boston,London (1991)
Skowron, A., Rauszer, C.: The discernibility matrices and functions in information systems. Intelligent Decision Support. Handbook of Applications and Advances of the Rough Set Theory. Edited by R. Slowinski. Kluwer Academic Publishers, Dordrecht,Boston, London (1992) 331–362
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Moshkov, M. (2001). Classification of Infinite Information Systems. In: Ziarko, W., Yao, Y. (eds) Rough Sets and Current Trends in Computing. RSCTC 2000. Lecture Notes in Computer Science(), vol 2005. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45554-X_23
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DOI: https://doi.org/10.1007/3-540-45554-X_23
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