Transforming Decision Rule Systems into Decision Trees: Syntactic Approach

Author:   Kerven Durdymyradov ,  Mikhail Moshkov ,  Azimkhon Ostonov
Publisher:   Springer Nature Switzerland AG
ISBN:  

9783032141170


Pages:   124
Publication Date:   13 April 2026
Format:   Hardback
Availability:   Not yet available   Availability explained
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Transforming Decision Rule Systems into Decision Trees: Syntactic Approach


Overview

This book is devoted to the transforming of decision rule systems into deterministic and nondeterministic decision trees that recognize the properties of these systems. It continues the development of the so-called syntactic approach to the study of the transformation problem, which assumes that the input data is unknown, and there is only a system of decision rules that must be transformed into decision trees. The book studies the depth and weighted depth of decision trees based on decision rule systems, and algorithms that model the operation of such decision trees for given tuples of attribute values. The results obtained in the book 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.

Full Product Details

Author:   Kerven Durdymyradov ,  Mikhail Moshkov ,  Azimkhon Ostonov
Publisher:   Springer Nature Switzerland AG
Imprint:   Springer Nature Switzerland AG
ISBN:  

9783032141170


ISBN 10:   3032141176
Pages:   124
Publication Date:   13 April 2026
Audience:   College/higher education ,  Professional and scholarly ,  Postgraduate, Research & Scholarly ,  Professional & Vocational
Format:   Hardback
Publisher's Status:   Forthcoming
Availability:   Not yet available   Availability explained
This item is yet to be released. You can pre-order this item and we will dispatch it to you upon its release.

Table of Contents

Introduction.- Six Problems of Transformation: Depth of Decision Trees.- Six Problems of Transformation: Weighted Depth of Decision Trees.

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