## A Comparison of Dynamic and non--Dynamic Rough Set Methods for Extracting Laws from Decision Tables (1998)

Citations: | 50 - 5 self |

### BibTeX

@INPROCEEDINGS{Bazan98acomparison,

author = {Jan G. Bazan},

title = { A Comparison of Dynamic and non--Dynamic Rough Set Methods for Extracting Laws from Decision Tables},

booktitle = {},

year = {1998},

pages = {321--365},

publisher = {Physica Verlag}

}

### Years of Citing Articles

### OpenURL

### Abstract

We report results of experiments on several data sets, in particular: Monk's problems data (see [58]), medical data (lymphography, breast cancer, primary tumor - see [30]) and StatLog's 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.