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On Minimal Inhibitory Rules for Almost All k-Valued Information Systems

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Moshkov M. J. , Skowron A. , Suraj Z.

Fundamenta Informaticae

2009

tom Vol. 93, nr 1-3

261-272

The minimal inhibitory rules for information systems can be used for construction of classifiers. We show that almost all information systems from a certain large class of information systems have relatively short minimal inhibitory rules. However, the number of such rules is not polynomial in the number of attributes and the number of objects. This class consists of all k-valued information systems, k ≥ 2, with the number of objects polynomial in the number of attributes. Hence, for efficient construction of classifiers some filtration techniques in rule generation are necessary. Another way is to work with lazy classification algorithms based on inhibitory rules.

On Minimal Rule Sets for Almost All Binary Information Systems

100%

Moshkov M. J. , Skowron A. , Suraj Z.

Fundamenta Informaticae

2007

tom Vol. 80, nr 1-3

247-258

The minimal rules for information systems are often used for inducing data models by methods in which the optimization of models is based on the minimal length principle. We show that almost all information systems from a certain large class of information systems have relatively short minimal rules. However, the number of such rules is not polynomial in the number of attributes and the number of objects. This class consists of all binary information systems with the number of objects polynomial in the number of attributes. Hence, for efficient inducing data models some filtration techniques in rule generation are necessary. In our further study we would like to extend our results for arbitrary information systems.