Lazy classification algorithms based on deterministic and inhibitory dicision rules

Pawel Delimata; Mikhail Ju Moshkov; Andrzej Skowron; Zbigniew Suraj

doi:10.1007/978-3-540-85638-2_8

Lazy classification algorithms based on deterministic and inhibitory dicision rules

Pawel Delimata^*, Mikhail Ju Moshkov, Andrzej Skowron, Zbigniew Suraj

^*Corresponding author for this work

Applied Mathematics and Computational Science

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

1 Scopus citations

Abstract

In this chapter, we consider the same classification problem as in Chaps. 5 and 6: for a given decision table T and a new object v it is required to generate a value of the decision attribute on v using values of conditional attributes on v. We compare two lazy [1] classification algorithms based on deterministic and inhibitory decision rules of the forms (a₁(x) = b₁) ∧...∧ (a_t(x) = b_t) → d(x) = b, respectively, where a₁,..., a_t are conditional attributes, b₁,..., b_t are values of these attributes, d is the decision attribute and b is a value of d. By Dec (T) we denote the set of values of the decision attribute d.

Original language	English (US)
Title of host publication	Inhibitory Rules in Data Analysis
Subtitle of host publication	A Rough Set Approach
Editors	Pawel Delimata, Zbigniew Suraj, Mikhail Moshkov, Andrzej Skowron
Pages	99-106+109-114
DOIs	https://doi.org/10.1007/978-3-540-85638-2_8
State	Published - 2009

Publication series

Name	Studies in Computational Intelligence
Volume	163
ISSN (Print)	1860-949X

ASJC Scopus subject areas

Artificial Intelligence

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10.1007/978-3-540-85638-2_8

Cite this

Delimata, P., Moshkov, M. J., Skowron, A., & Suraj, Z. (2009). Lazy classification algorithms based on deterministic and inhibitory dicision rules. In P. Delimata, Z. Suraj, M. Moshkov, & A. Skowron (Eds.), Inhibitory Rules in Data Analysis: A Rough Set Approach (pp. 99-106+109-114). (Studies in Computational Intelligence; Vol. 163). https://doi.org/10.1007/978-3-540-85638-2_8

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abstract = "In this chapter, we consider the same classification problem as in Chaps. 5 and 6: for a given decision table T and a new object v it is required to generate a value of the decision attribute on v using values of conditional attributes on v. We compare two lazy [1] classification algorithms based on deterministic and inhibitory decision rules of the forms (a1(x) = b1) ∧...∧ (at(x) = bt) → d(x) = b, respectively, where a1,..., at are conditional attributes, b1,..., bt are values of these attributes, d is the decision attribute and b is a value of d. By Dec (T) we denote the set of values of the decision attribute d.",

author = "Pawel Delimata and Moshkov, {Mikhail Ju} and Andrzej Skowron and Zbigniew Suraj",

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Lazy classification algorithms based on deterministic and inhibitory dicision rules. / Delimata, Pawel; Moshkov, Mikhail Ju; Skowron, Andrzej et al.
Inhibitory Rules in Data Analysis: A Rough Set Approach. ed. / Pawel Delimata; Zbigniew Suraj; Mikhail Moshkov; Andrzej Skowron. 2009. p. 99-106+109-114 (Studies in Computational Intelligence; Vol. 163).

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

TY - CHAP

T1 - Lazy classification algorithms based on deterministic and inhibitory dicision rules

AU - Delimata, Pawel

AU - Moshkov, Mikhail Ju

AU - Skowron, Andrzej

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N2 - In this chapter, we consider the same classification problem as in Chaps. 5 and 6: for a given decision table T and a new object v it is required to generate a value of the decision attribute on v using values of conditional attributes on v. We compare two lazy [1] classification algorithms based on deterministic and inhibitory decision rules of the forms (a1(x) = b1) ∧...∧ (at(x) = bt) → d(x) = b, respectively, where a1,..., at are conditional attributes, b1,..., bt are values of these attributes, d is the decision attribute and b is a value of d. By Dec (T) we denote the set of values of the decision attribute d.

AB - In this chapter, we consider the same classification problem as in Chaps. 5 and 6: for a given decision table T and a new object v it is required to generate a value of the decision attribute on v using values of conditional attributes on v. We compare two lazy [1] classification algorithms based on deterministic and inhibitory decision rules of the forms (a1(x) = b1) ∧...∧ (at(x) = bt) → d(x) = b, respectively, where a1,..., at are conditional attributes, b1,..., bt are values of these attributes, d is the decision attribute and b is a value of d. By Dec (T) we denote the set of values of the decision attribute d.

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T3 - Studies in Computational Intelligence

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A2 - Delimata, Pawel

A2 - Suraj, Zbigniew

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A2 - Skowron, Andrzej

ER -

Lazy classification algorithms based on deterministic and inhibitory dicision rules

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