DocumentCode :
2252597
Title :
Sequential optimization of γ-decision rules
Author :
Zielosko, B.
Author_Institution :
Math. & Comput. Sci. & Eng. Div., King Abdullah Univ. of Sci. & Technol., Thuwal, Saudi Arabia
fYear :
2012
fDate :
9-12 Sept. 2012
Firstpage :
339
Lastpage :
346
Abstract :
The paper is devoted to the study of an extension of dynamic programming approach which allows sequential optimization of approximate decision rules relative to length, coverage and number of misclassifications. Presented algorithm constructs a directed acyclic graph Δγ(T) which nodes are subtables of the decision table T. Based on the graph Δγ(T) we can describe all irredundant γ-decision rules with minimum length, after that among these rules describe all rules with maximum coverage, and among such rules describe all rules with minimum number of misclassifications. We can also change the set of cost functions and order of optimization. Sequential optimization can be considered as tool that help to construct simpler rules for understanding and interpreting by experts.
Keywords :
decision tables; decision theory; dynamic programming; graph theory; γ-decision rules; cost functions; decision table; dynamic programming approach; graph theory; sequential optimization; Accuracy; Cost function; Dynamic programming; Educational institutions; Presses; Uncertainty;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Science and Information Systems (FedCSIS), 2012 Federated Conference on
Conference_Location :
Wroclaw
Print_ISBN :
978-1-4673-0708-6
Electronic_ISBN :
978-83-60810-51-4
Type :
conf
Filename :
6354493
Link To Document :
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