@INPROCEEDINGS { Rsds4558,
author = {Liang, Jiye and Qian, Yuhua}, 
title = {Evaluation Method for Decision Rule Sets}, 
booktitle = {Proceedings of the 11th International Conference on Rough Sets, Fuzzy Sets, Data Mining and Granular Computing (RSFDGrC'2007)}, 
series =  = {Lecture Notes in Artificial Intelligence}, 
volume = 4482, 
pages = {272--279}, 
publisher = {Springer-Verlag}, 
address = {Heidelberg - Berlin, Germany}, 
year = 2007, 
editor = {An, A. and Stefanowski, Jerzy and Ramanna, Sheela and Butz, C. and Pedrycz, Witold and Wang, Guoying}, 
isbn = {978-3-540-72529-9}, 
abstract = {In this paper, a decision table in rough set theory is classified into three types according to its consistency. Three parameters alpha (whole certainty measure), eta (whole consistency measure) and gamma (whole support measure) are introduced to evaluate the performance of a decision rule set induced from a decision table. For three types of decision tables, the dependency of the parameters upon condition/decision granulation is analyzed. The parameters can be used to construct an evaluation function in favor of selecting a better one from some different rule acquiring methods for real decision problems.}, 
keywords = {rough set theory, decision table, decision rule, knowledge granulation, decision evaluation, }, 
}