New book by KAUST Ph.D. Students Kerven Durdymyradov, Azimkhon Ostonov, and Professor Mikhail Moshkov published by Springer

About

A new book titled Decision Trees Versus Systems of Decision Rules: A Rough Set Approach by Kerven Durdymyradov, Mikhail Moshkov, and Azimkhon Ostonov has been published by Springer.

Decision trees and systems of decision rules are widely used to represent knowledge, as classifiers that predict decisions for new objects, as well as algorithms for solving various problems such as fault diagnosis, combinatorial optimization, and more. These models are among the most interpretable forms of knowledge representation and classification. Investigating the relationships between these two models is an important task in computer science.

This book explores, within the framework of rough set theory, the complexity of decision trees and decision rule systems, as well as the relationships between them in problems involving information systems, decision tables from closed classes, and formal languages. The possibilities of transforming decision rule systems into decision trees are studied in detail. The results are useful for researchers working with decision trees and decision rule systems in data analysis, especially in rough set theory, logical analysis of data, and test theory. This book can also be used to develop courses for graduate students.