Abstract
In this chapter, we consider some reductions which will be used later in the investigations of decision trees for problems. We show that, in the frameworks of the local approach, the study of decision trees for problems can be reduced to the study of decision trees for decision tables. We prove that, instead of arbitrary classes of information systems, we can consider classes containing only one information system. We also show that the matrix of upper local bounds for a sccf-triple completely defines its matrix of lower local bounds and vice versa. In particular, the local upper type of a sccf-triple completely defines its local lower type and vice versa.
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References
Moshkov, M.: Comparative analysis of deterministic and nondeterministic decision tree complexity, Global approach. Fundam. Inform. 25(2), 201–214 (1996)
Moshkov, M.: Comparative analysis of deterministic and nondeterministic decision tree complexity, Local approach. In: Peters, J.F., Skowron, A. (eds.) Transactions on Rough Sets IV, Lecture Notes in Computer Science, vol. 3700, pp. 125–143. Springer, Berlin (2005)
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Moshkov, M. (2020). Main Reductions. In: Comparative Analysis of Deterministic and Nondeterministic Decision Trees. Intelligent Systems Reference Library, vol 179. Springer, Cham. https://doi.org/10.1007/978-3-030-41728-4_10
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DOI: https://doi.org/10.1007/978-3-030-41728-4_10
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