Abstract
In the paper, an idea of modified dynamic programming algorithm is used for optimization of exact decision rules relative to length. The aims of the paper are: (i) study a length of decision rules, and (ii) study a size of a directed acyclic graph (the number of nodes and edges). The paper contains experimental results with decision tables from UCI Machine Learning Repository and comparison with results for dynamic programming algorithm.
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Zielosko, B. (2018). Optimization of Exact Decision Rules Relative to Length. In: Czarnowski, I., Howlett, R., Jain, L. (eds) Intelligent Decision Technologies 2017. IDT 2017. Smart Innovation, Systems and Technologies, vol 72. Springer, Cham. https://doi.org/10.1007/978-3-319-59421-7_14
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DOI: https://doi.org/10.1007/978-3-319-59421-7_14
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