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Transactions on Rough Sets XII pp 90–105Cite as

Comparison of Some Classification Algorithms Based on Deterministic and Nondeterministic Decision Rules

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Part of the book series: Lecture Notes in Computer Science ((TRS,volume 6190))

Abstract

We discuss two, in a sense extreme, kinds of nondeterministic rules in decision tables. The first kind of rules, called as inhibitory rules, are blocking only one decision value (i.e., they have all but one decisions from all possible decisions on their right hand sides). Contrary to this, any rule of the second kind, called as a bounded nondeterministic rule, can have on the right hand side only a few decisions. We show that both kinds of rules can be used for improving the quality of classification. 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. We also present an application of bounded nondeterministic rules in construction of rule based classifiers. We include the results of experiments showing that by combining rule based classifiers based on minimal decision rules with bounded nondeterministic rules having confidence close to 1 and sufficiently large support, it is possible to improve the classification quality.

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Author information

Authors and Affiliations

  1. Chair of Computer Science, University of Rzeszów, Rejtana 16A, 35-310, Rzeszów, Poland

    Paweł Delimata & Zbigniew Suraj

  2. Institute of Computer Science, University of Silesia, Bȩdzińska 39, 41-200, Sosnowiec, Poland

    Barbara Marszał-Paszek & Piotr Paszek

  3. Division of Mathematical and Computer Sciences and Engineering, King Abdullah University of Science and Technology, P.O. Box 55455, Jeddah, 21534, Saudi Arabia

    Mikhail Moshkov

  4. Institute of Mathematics, Warsaw University, Banacha 2, 02-097, Warsaw, Poland

    Andrzej Skowron

Authors
  1. Paweł Delimata
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  2. Barbara Marszał-Paszek
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  3. Mikhail Moshkov
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  4. Piotr Paszek
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  5. Andrzej Skowron
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  6. Zbigniew Suraj
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Editor information

Editors and Affiliations

  1. Department of Electrical and Computer Engineering, University of Manitoba, Winnipeg, R3T 5V6, Manitoba, Canada

    James F. Peters

  2. Institute of Mathematics, Warsaw University, Banacha 2, 02-097, Warsaw, Poland

    Andrzej Skowron

  3. Insitute of Computing Science, Laboratory of Intelligent Decision Support Systems, Poznań University of Technology, Piotrowo 2, 60-965, Poznań, Poland

    Roman Słowiński

  4. Department of Mathematics and Computing Science, Saint Mary’s University, B3H 3C3, Halifax, NS, Canada

    Pawan Lingras

  5. School of Electronics and Information Engineering, Tongji University, 201804, Shanghai, P.R. China

    Duoqian Miao

  6. Faculty of Medicine, Department of Medical Informatics, 89-1 Enya-cho, Shimane University, 693-8501, Izumo, Japan

    Shusaku Tsumoto

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Delimata, P., Marszał-Paszek, B., Moshkov, M., Paszek, P., Skowron, A., Suraj, Z. (2010). Comparison of Some Classification Algorithms Based on Deterministic and Nondeterministic Decision Rules. In: Peters, J.F., Skowron, A., Słowiński, R., Lingras, P., Miao, D., Tsumoto, S. (eds) Transactions on Rough Sets XII. Lecture Notes in Computer Science, vol 6190. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14467-7_5

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  • DOI: https://doi.org/10.1007/978-3-642-14467-7_5

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-14466-0

  • Online ISBN: 978-3-642-14467-7

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