KAUST researchers publish new book on decision rule systems

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KAUST Postdoctoral Research Fellows Kerven Durdymyradov and Azimkhon Ostonov, along with Professor Mikhail Moshkov, have published a new book with Springer titled "Transforming Decision Rule Systems into Decision Trees: Syntactic Approach."

The book is devoted to the transformation of decision rule systems into deterministic and nondeterministic decision trees that recognize the properties of these systems. It continues the development of the syntactic approach to the study of the transformation problem, which assumes the input data is unknown and only a system of decision rules exists to be transformed.

The authors study the depth and weighted depth of decision trees based on decision rule systems and algorithms that model the operation of such trees for given tuples of attribute values. The results may be useful for researchers using 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 create courses for graduate students.

Read the book here.