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Decision and Inhibitory Trees and Rules for Decision Tables with Many-valued Decisions: Intelligent Systems Reference Library, cartea 156

Autor Fawaz Alsolami, Mohammad Azad, Igor Chikalov, Mikhail Moshkov
en Limba Engleză Paperback – 27 noi 2020
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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Specificații

ISBN-13: 9783030128562
ISBN-10: 3030128563
Pagini: 276
Ilustrații: XVII, 276 p. 44 illus., 8 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.42 kg
Ediția:1st ed. 2020
Editura: Springer International Publishing
Colecția Springer
Seria Intelligent Systems Reference Library

Locul publicării:Cham, Switzerland

Cuprins

As in MS. 

Textul de pe ultima copertă

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.


Caracteristici

Presents a revealing study on decision and inhibitory trees and rules for decision tables with many-valued decisions Provides various examples of problems and decision tables with many-valued decisions Studies the time complexity of decision and inhibitory trees and rule systems over arbitrary sets of attributes represented by information systems