Decision and Inhibitory Trees and Rules for Decision Tables with Many-valued Decisions
Language: English
Published by Springer, 2019
Series: Book 127 of 188 - Intelligent Systems Reference Library
- Hardcover
- Used
Condition: Used - Fine
US$ 25.50
Quantity: 1 available
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Zustand: Sehr gut | Seiten: 296 | Sprache: Englisch | Produktart: Bücher | 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.
Seller Inventory # 33403071/2
- Title
- Decision and Inhibitory Trees and Rules for Decision Tables with Many-valued Decisions
- Author
- Azad, Mohammad
- Publisher
- Springer
- Publication year
- 2019
- Condition
- Sehr gut
- Binding
- Hardcover
- Language
- English
- ISBN 10
- 3030128539
- ISBN 13
- 9783030128531
- Series
- Book 127 of 188: Intelligent Systems Reference Library
- Seller catalogs
- Bücher
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.
"Synopsis" may belong to another edition of this title.
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 the title" may belong to another edition of this title.
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