New book "Decision and Inhibitory Trees and Rules for Decision Tables with Many-valued Decisions" by Fawaz Alsolami, Mohammad Azad, Igor Chikalov, and Mikhail Moshkov is published by Springer: https://link.springer.com/book/10.1007/978-3-030-12854-8
The results presented in this book (including the consideration of a new tool - inhibitory trees) can be useful for researchers in data mining, knowledge discovery, and machine learning, especially those who study decision tables with many-valued decisions. We consider various examples of problems and corresponding decision tables with many-valued decisions, discuss the difference between decision and inhibitory trees and rules, and create tools for their design and analysis. Applications include the study of totally optimal (optimal relative to a number of criteria simultaneously) decision and inhibitory trees and rules, the comparison of greedy heuristics for tree and rule construction as a single-criterion and bi-criteria optimization algorithms, the development of the restricted multi-pruning approach used in classification and knowledge representation.
