Construction of α-decision trees for tables with many-valued decisions

Mikhail Moshkov; Beata Zielosko

doi:10.1007/978-3-642-24425-4_63

Construction of α-decision trees for tables with many-valued decisions

Mikhail Moshkov, Beata Zielosko

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

7 Scopus citations

Abstract

The paper is devoted to the study of greedy algorithm for construction of approximate decision trees (α-decision trees). This algorithm is applicable to decision tables with many-valued decisions where each row is labeled with a set of decisions. For a given row, we should find a decision from the set attached to this row. We consider bound on the number of algorithm steps, and bound on the algorithm accuracy relative to the depth of decision trees. © 2011 Springer-Verlag.

Original language	English (US)
Title of host publication	Rough Sets and Knowledge Technology
Publisher	Springer Nature
Pages	486-494
Number of pages	9
ISBN (Print)	9783642244247
DOIs	https://doi.org/10.1007/978-3-642-24425-4_63
State	Published - 2011

Bibliographical note

KAUST Repository Item: Exported on 2020-10-01

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

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10.1007/978-3-642-24425-4_63

Cite this

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title = "Construction of α-decision trees for tables with many-valued decisions",

abstract = "The paper is devoted to the study of greedy algorithm for construction of approximate decision trees (α-decision trees). This algorithm is applicable to decision tables with many-valued decisions where each row is labeled with a set of decisions. For a given row, we should find a decision from the set attached to this row. We consider bound on the number of algorithm steps, and bound on the algorithm accuracy relative to the depth of decision trees. {\textcopyright} 2011 Springer-Verlag.",

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AU - Zielosko, Beata

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Y1 - 2011

N2 - The paper is devoted to the study of greedy algorithm for construction of approximate decision trees (α-decision trees). This algorithm is applicable to decision tables with many-valued decisions where each row is labeled with a set of decisions. For a given row, we should find a decision from the set attached to this row. We consider bound on the number of algorithm steps, and bound on the algorithm accuracy relative to the depth of decision trees. © 2011 Springer-Verlag.

AB - The paper is devoted to the study of greedy algorithm for construction of approximate decision trees (α-decision trees). This algorithm is applicable to decision tables with many-valued decisions where each row is labeled with a set of decisions. For a given row, we should find a decision from the set attached to this row. We consider bound on the number of algorithm steps, and bound on the algorithm accuracy relative to the depth of decision trees. © 2011 Springer-Verlag.

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UR - http://link.springer.com/10.1007/978-3-642-24425-4_63

UR - http://www.scopus.com/inward/record.url?scp=80054052966&partnerID=8YFLogxK

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DO - 10.1007/978-3-642-24425-4_63

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SP - 486

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BT - Rough Sets and Knowledge Technology

PB - Springer Nature

ER -

Construction of α-decision trees for tables with many-valued decisions

Abstract

Bibliographical note

ASJC Scopus subject areas

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