Abstract
Decision rules can be characterized by many parameters. This chapter presents a dynamic programming algorithm that can sequentially optimize decision rules with respect to multiple criteria. In some cases, we can find decision rules that are simultaneously optimal with respect to multiple criteria. We consider this phenomenon when dealing with length and coverage. This chapter also contains a simulation of a greedy algorithm for the construction of relatively small sets of decision rules. The work of this algorithm can be used to adapt a nontrivial lower bound on the minimum cardinality for partial covers to the construction of systems of decision rules.
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AbouEisha, H., Amin, T., Chikalov, I., Hussain, S., Moshkov, M. (2019). Multi-stage Optimization of Decision Rules. In: Extensions of Dynamic Programming for Combinatorial Optimization and Data Mining. Intelligent Systems Reference Library, vol 146. Springer, Cham. https://doi.org/10.1007/978-3-319-91839-6_10
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DOI: https://doi.org/10.1007/978-3-319-91839-6_10
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