Discovery of Decision Rules by Matching New Objects Against Data Tables

Authors:
Jan G. Bazan
Affiliations:
-
Venue:
RSCTC '98 Proceedings of the First International Conference on Rough Sets and Current Trends in Computing
Year:
1998

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Abstract

In this paper we present an exemplary algorithm classifying new objects by matching them directly against data table to generate relevant decision instead of matching it against all rules generated from data table (see [1]). We report results of experiments on three medical data sets, concerning lymphography, breast cancer and primary tumor (see [8]). We compare standard methods for extracting laws from decision tables (see e.g. [17], [1]), based on rough set (see [13]) and boolean reasoning (see [2]), with the method based on algorithms calculating relevant decision rules for new objects. 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.