Title :
On Learning Decision Rules From Flow Graphs
Author :
Chan, Chien-Chung ; Tsumoto, Shusaku
Author_Institution :
Akron Univ., Akron
Abstract :
The use of flow graphs to represent information flow distribution from data tables for intelligent data analysis was first proposed by Pawlak. This paper studies the representation of flow graphs by multiset decision tables. This representation is minimal. Inspired by the flow graphs, a new rule learning algorithm based on this representation is presented with examples. Two sets of rules are learned from certain examples and examples in the boundary set. Rules are characterized by Bayesian factors introduced by Pawlak.
Keywords :
data analysis; graph theory; data tables; flow distribution; flow graphs; intelligent data analysis; learning decision rules; multiset decision tables; Bayesian methods; Biomedical informatics; Computer science; Data analysis; Data flow computing; Decision trees; Flow graphs; Information systems; Rough sets;
Conference_Titel :
Fuzzy Information Processing Society, 2007. NAFIPS '07. Annual Meeting of the North American
Conference_Location :
San Diego, CA
Print_ISBN :
1-4244-1213-7
Electronic_ISBN :
1-4244-1214-5
DOI :
10.1109/NAFIPS.2007.383918
