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Decision and Inhibitory Trees and Rules for Decision Tables with Many-valued Decisions (Intelligent Systems Reference Library, 156) - Softcover

Book 127 of 188: Intelligent Systems Reference Library

Alsolami, Fawaz; Azad, Mohammad; Chikalov, Igor; Moshkov, Mikhail

 
9783030128562: Decision and Inhibitory Trees and Rules for Decision Tables with Many-valued Decisions (Intelligent Systems Reference Library, 156)
Softcover
ISBN 10: 3030128563 ISBN 13: 9783030128562
Publisher: Springer, 2020

Synopsis

The results presented here (including the assessment of a new tool – inhibitory trees) offer valuable tools for researchers in the areas of data mining, knowledge discovery, and machine learning, especially those whose work involves decision tables with many-valued decisions. The authors consider various examples of problems and corresponding decision tables with many-valued decisions, discuss the difference between decision and inhibitory trees and rules, and develop tools for their analysis and design. Applications include the study of totally optimal (optimal in relation to a number of criteria simultaneously) decision and inhibitory trees and rules; the comparison of greedy heuristics for tree and rule construction as single-criterion and bi-criteria optimization algorithms; and the development of a restricted multi-pruning approach used in classification and knowledge representation.


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From the Back Cover

The results presented here (including the assessment of a new tool – inhibitory trees) offer valuable tools for researchers in the areas of data mining, knowledge discovery, and machine learning, especially those whose work involves decision tables with many-valued decisions. The authors consider various examples of problems and corresponding decision tables with many-valued decisions, discuss the difference between decision and inhibitory trees and rules, and develop tools for their analysis and design. Applications include the study of totally optimal (optimal in relation to a number of criteria simultaneously) decision and inhibitory trees and rules; the comparison of greedy heuristics for tree and rule construction as single-criterion and bi-criteria optimization algorithms; and the development of a restricted multi-pruning approach used in classification and knowledge representation.


"About this title" may belong to another edition of this title.

Publisher
Springer
Publication date
2020
Language
English
ISBN 10 
3030128563
ISBN 13 
9783030128562
Binding
Paperback
Edition number
1
Number of pages
293