Optimization of Decision Rule Complexity for Decision Tables with Many-Valued Decisions

Author

Azad, Mohammad ; Chikalov, Igor ; Moshkov, Mikhail

Author_Institution

Comput., Electr. & Math. Sci. & Eng. Div., King Abdullah Univ. of Sci. & Technol., Thuwal, Saudi Arabia

fYear

2013

fDate

13-16 Oct. 2013

Firstpage

444

Lastpage

448

Abstract

We describe new heuristics to construct decision rules for decision tables with many-valued decisions from the point of view of length and coverage which are enough good. We use statistical test to find leaders among the heuristics. After that, we compare our results with optimal result obtained by dynamic programming algorithms. The average percentage of relative difference between length (coverage) of constructed and optimal rules is at most 6.89% (15.89%, respectively) for leaders which seems to be a promising result.

Keywords

computational complexity; decision tables; dynamic programming; statistical testing; coverage point-of-view; decision rule complexity; decision tables; dynamic programming algorithms; length point-of-view; many-valued decisions; statistical test; Clustering algorithms; Dynamic programming; Flyback transformers; Greedy algorithms; Heuristic algorithms; Machine learning algorithms; Optimization; Optimization; decision rules; dynamic programming; greedy heuristics; many-valued decisions;

fLanguage

English

Publisher

ieee

Conference_Titel

Systems, Man, and Cybernetics (SMC), 2013 IEEE International Conference on

Conference_Location

Manchester

Type

conf

DOI

10.1109/SMC.2013.81

Filename

6721835