Three approaches to handle inconsistency in decision tables

Fawaz Alsolami; Mohammad Azad; Igor Chikalov; Mikhail Moshkov

doi:10.1007/978-3-030-12854-8_3

Three approaches to handle inconsistency in decision tables

Fawaz Alsolami^*, Mohammad Azad, Igor Chikalov, Mikhail Moshkov

^*Corresponding author for this work

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

Abstract

In this chapter, we discuss main notions related to inconsistent decision tables, and three approaches to handle inconsistency in decision tables: decision tables with many-valued decisions (MVD approach), decision tables with generalized decisions (GD approach), and decision tables with most common decisions (MCD approach). After that, we compare complexity and classification accuracy of decision trees constructed by greedy heuristics in the frameworks of these approaches.

Original language	English (US)
Title of host publication	Intelligent Systems Reference Library
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	37-44
Number of pages	8
DOIs	https://doi.org/10.1007/978-3-030-12854-8_3
State	Published - 2020

Publication series

Name	Intelligent Systems Reference Library
Volume	156
ISSN (Print)	1868-4394
ISSN (Electronic)	1868-4408

Bibliographical note

Publisher Copyright:
© 2020, Springer Nature Switzerland AG.

ASJC Scopus subject areas

General Computer Science
Information Systems and Management
Library and Information Sciences

Access to Document

10.1007/978-3-030-12854-8_3

Cite this

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AB - In this chapter, we discuss main notions related to inconsistent decision tables, and three approaches to handle inconsistency in decision tables: decision tables with many-valued decisions (MVD approach), decision tables with generalized decisions (GD approach), and decision tables with most common decisions (MCD approach). After that, we compare complexity and classification accuracy of decision trees constructed by greedy heuristics in the frameworks of these approaches.

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M3 - Chapter

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Three approaches to handle inconsistency in decision tables

Abstract

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