Comparison of lazy classification algorithms based on deterministic and inhibitory decision rules

Authors:
Paweł Delimata;Mikhail Moshkov;Andrzej Skowron;Zbigniew Suraj
Affiliations:
Computer Science, University of Rzeszów, Rzeszów, Poland;Institute of Computer Science, University of Silesia, Sosnowiec, Poland;Institute of Mathematics, Warsaw University, Warsaw, Poland;Computer Science, University of Rzeszów, Rzeszów, Poland
Venue:
RSKT'08 Proceedings of the 3rd international conference on Rough sets and knowledge technology
Year:
2008

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Abstract

In the paper, two lazy classification algorithms of polynomial time complexity are considered. These algorithms are based on deterministic and inhibitory decision rules, but the direct generation of rules is not required. Instead of this, for any new object the considered algorithms extract from a given decision table efficiently some information about the set of rules. Next, this information is used by a decision-making procedure. The reported results of experiments show that the algorithms based on inhibitory decision rules are often better than those based on deterministic decision rules.