Decision and Inhibitory Trees and Rules for Decision Tables with Many-valued Decisions

1. Auflage 2020
ISBN: 978-3-030-12853-1
Verlag: Springer

Buch, Englisch, Band 156, 276 Seiten, Format (B × H): 160 mm x 241 mm, Gewicht: 612 g

Reihe: Intelligent Systems Reference Library

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.

Zielgruppe

Research

Autoren/Hrsg.

Alsolami, Fawaz

Azad, Mohammad

Chikalov, Igor

Moshkov, Mikhail

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Maschinelles Lernen
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Data Mining
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Wissensbasierte Systeme, Expertensysteme

Inhaltsverzeichnis

As in MS.