@INCOLLECTION { Rsds2884,
author = {Bazan, Jan G.}, 
title = {A Comparison and non-Dynamic Rough Set Method for Extracting Laws Decision Tables}, 
booktitle = {Rough Sets in Knowledge Discovery 1. Methodology and Applications}, 
series =  = {Studies in Fuzziness and Soft Computing}, 
pages = {321--365}, 
publisher = {Physica-Verlag}, 
address = {Heidelberg, Germany}, 
year = 1998, 
editor = {Polkowski, Lech and Skowron, Andrzej}, 
isbn = {3-7908-1119-X}, 
abstract = {We report results of experiments on several data sets, in particular: Monk's problems data (see [58]), medical data (see [32]). We compare standard methods for extracting laws from decision tables (see [43], [52]), based on rough set (see [42]), and Boolean reasoning (see [8]), with the method based on dynamic reducts and dynamic rules (see [3], [4], [5], [6]). We also compare the results of computer experiments on those data sets obtained by applying our system based on rough set methods with the results on the same data sets obtained with help of several data analysis systems known from literature.}, 
keywords = {knowledge discovery, rough sets, classification algorithms, machine learning, }, 
}