Zbigniew Suraj

Institute of Computer Science

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Andrzej Skowron

Polish Academy of Sciences

Piotr Grochowalski

Rzeszów University

Krzysztof Pancerz

John Paul II Catholic University of Lublin

Mikhail Moshkov

King Abdullah University of Science and Technology

Paweł Delimata

Institute of Computer Science

James F. Peters

University of Manitoba

Sheela Ramanna

University of Winnipeg

Maciej Borkowski

Warsaw University of Life Sciences

Yurii Bloshko

Rzeszów University

Sibasis Bandyopadhyay

Midnapore Medical College and Hospital

Cooperative Institutions

Institute of Computer Science

Rzeszów University

Institute of Mathematics

Polish Academy of Sciences

University of Warsaw

Systems Research Institute

University of Manitoba

University of Information Technology and Management in Rzeszow

University of Regina

KES International

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Comparison of Lazy Classification Algorithms Based on Deterministic and Inhibitory Decision Rules

Rough Sets and Knowledge Technology (2008)

Paweł Delimata Mikhail Moshkov Andrzej Skowron Zbigniew Suraj

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.

Decision table

Decision rule

Decision system

10.1007/978-3-540-79721-0_13

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Citations (9)

Approximate Petri Nets for Rule-Based Decision Making

Lecture notes in computer science (2004)

Barbara Fryc Krzysztof Pancerz Zbigniew Suraj

Process architecture

Stochastic Petri net

Net (polyhedron)

Representation

Petri dish

10.1007/978-3-540-25929-9_93

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Citations (14)

Two Families of Classification Algorithms

Lecture notes in computer science (2007)

Paweł Delimata Mikhail Moshkov Andrzej Skowron Zbigniew Suraj

10.1007/978-3-540-72530-5_35

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Citations (14)

On Minimal Rule Sets for Almost All Binary Information Systems

Fundamenta Informaticae (2007)

Mikhail Moshkov Andrzej Skowron Zbigniew Suraj

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.

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Citations (11)

The Rough Set Database System

Transactions on rough sets (2008)

Zbigniew Suraj Piotr Grochowalski

Bibliography

10.1007/978-3-540-85064-9_14

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Rough Sets for Discovering Concurrent System Models from Data Tables

IGI Global eBooks (2011)

Krzysztof Pancerz Zbigniew Suraj

This chapter constitutes the continuation of a new research trend binding rough set theory with concurrency theory. In general, this trend concerns the following problems: discovering concurrent system models from experimental data represented by information systems, dynamic information systems or specialized matrices, a use of rough set methods for extracting knowledge from data, a use of rules for describing system behaviors, and modeling and analyzing of concurrent systems by means of Petri nets on the basis of extracted rules. Some automatized methods of discovering concurrent system models from data tables are presented. Data tables are created on the basis of observations or specifications of process behaviors in the modeled systems. Proposed methods are based on rough set theory and colored Petri net theory.

Continuation

Basis (linear algebra)

10.4018/978-1-59904-552-8.ch012

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Citations (11)

Discovering Concurrent Process Models in Data: A Rough Set Approach

Lecture notes in computer science (2009)

Zbigniew Suraj

Presentation (obstetrics)

10.1007/978-3-642-10646-0_2

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Citations (5)