Mikhail Moshkov's Books

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

By: Fawaz Alsolami,Mohammad Azad,Igor Chikalov,Mikhail Moshkov

Write a review Read reviews Take a Quiz Solve Book Puzzle

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

By: Fawaz Alsolami,Mohammad Azad,Igor Chikalov,Mikhail Moshkov

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.

Average ratings

N/A

Write a review

Solve jigsaw puzzle

Age

Page Count

280

Publisher

Springer

Published Date

ISBN 10

3030128547

ISBN 13

9783030128548

Dynamic Programming Multi-Objective Combinatorial Optimization

By: Michal Mankowski,Mikhail Moshkov

Write a review Read reviews Take a Quiz Solve Book Puzzle

Dynamic Programming Multi-Objective Combinatorial Optimization

By: Michal Mankowski,Mikhail Moshkov

This book introduces a fairly universal approach to the design and analysis of exact optimization algorithms for multi-objective combinatorial optimization problems. It proposes the circuits without repetitions representing the sets of feasible solutions along with the increasing and strictly increasing cost functions as a model for such problems. The book designs the algorithms for multi-stage and bi-criteria optimization and for counting the solutions in the framework of this model. As applications, this book studies eleven known combinatorial optimization problems: matrix chain multiplication, global sequence alignment, optimal paths in directed graphs, binary search trees, convex polygon triangulation, line breaking (text justification), one-dimensional clustering, optimal bitonic tour, segmented least squares, optimization of matchings in trees, and 0/1 knapsack problem. The results presented are useful for researchers in combinatorial optimization. This book is also useful as the basis for graduate courses.

Average ratings

N/A

Write a review

Solve jigsaw puzzle

Age

Page Count

213

Publisher

Springer Nature

Published Date

ISBN 10

3030639207

ISBN 13

9783030639204

Combinatorial Machine Learning

A Rough Set Approach

By: Mikhail Moshkov,Beata Zielosko

Write a review Read reviews Take a Quiz Solve Book Puzzle

Combinatorial Machine Learning

A Rough Set Approach

By: Mikhail Moshkov,Beata Zielosko

Decision trees and decision rule systems are widely used in different applications as algorithms for problem solving, as predictors, and as a way for knowledge representation. Reducts play key role in the problem of attribute (feature) selection. The aims of this book are (i) the consideration of the sets of decision trees, rules and reducts; (ii) study of relationships among these objects; (iii) design of algorithms for construction of trees, rules and reducts; and (iv) obtaining bounds on their complexity. Applications for supervised machine learning, discrete optimization, analysis of acyclic programs, fault diagnosis, and pattern recognition are considered also. This is a mixture of research monograph and lecture notes. It contains many unpublished results. However, proofs are carefully selected to be understandable for students. The results considered in this book can be useful for researchers in machine learning, data mining and knowledge discovery, especially for those who are working in rough set theory, test theory and logical analysis of data. The book can be used in the creation of courses for graduate students.

Average ratings

N/A

Write a review

Solve jigsaw puzzle

Age

Page Count

186

Publisher

Springer

Published Date

ISBN 10

3642209955

ISBN 13

9783642209956

Three Approaches to Data Analysis

Test Theory, Rough Sets and Logical Analysis of Data

By: Igor Chikalov,Vadim Lozin,Irina Lozina,Mikhail Moshkov,Hung Son Nguyen,Andrzej Skowron,Beata Zielosko

Write a review Read reviews Take a Quiz Solve Book Puzzle

Three Approaches to Data Analysis

Test Theory, Rough Sets and Logical Analysis of Data

By: Igor Chikalov,Vadim Lozin,Irina Lozina,Mikhail Moshkov,Hung Son Nguyen,Andrzej Skowron,Beata Zielosko

In this book, the following three approaches to data analysis are presented: - Test Theory, founded by Sergei V. Yablonskii (1924-1998); the first publications appeared in 1955 and 1958, - Rough Sets, founded by Zdzisław I. Pawlak (1926-2006); the first publications appeared in 1981 and 1982, - Logical Analysis of Data, founded by Peter L. Hammer (1936-2006); the first publications appeared in 1986 and 1988. These three approaches have much in common, but researchers active in one of these areas often have a limited knowledge about the results and methods developed in the other two. On the other hand, each of the approaches shows some originality and we believe that the exchange of knowledge can stimulate further development of each of them. This can lead to new theoretical results and real-life applications and, in particular, new results based on combination of these three data analysis approaches can be expected. - Logical Analysis of Data, founded by Peter L. Hammer (1936-2006); the first publications appeared in 1986 and 1988. These three approaches have much in common, but researchers active in one of these areas often have a limited knowledge about the results and methods developed in the other two. On the other hand, each of the approaches shows some originality and we believe that the exchange of knowledge can stimulate further development of each of them. This can lead to new theoretical results and real-life applications and, in particular, new results based on combination of these three data analysis approaches can be expected. These three approaches have much in common, but researchers active in one of these areas often have a limited knowledge about the results and methods developed in the other two. On the other hand, each of the approaches shows some originality and we believe that the exchange of knowledge can stimulate further development of each of them. This can lead to new theoretical results and real-life applications and, in particular, new results based on combination of these three data analysis approaches can be expected.

Average ratings

N/A

Write a review

Solve jigsaw puzzle

Age

Page Count

209

Publisher

Springer Science & Business Media

Published Date

ISBN 10

3642286674

ISBN 13

9783642286674

Decision Trees with Hypotheses

By: Mohammad Azad,Igor Chikalov,Shahid Hussain,Mikhail Moshkov,Beata Zielosko

Write a review Read reviews Take a Quiz Solve Book Puzzle

Decision Trees with Hypotheses

By: Mohammad Azad,Igor Chikalov,Shahid Hussain,Mikhail Moshkov,Beata Zielosko

In this book, the concept of a hypothesis about the values of all attributes is added to the standard decision tree model, considered, in particular, in test theory and rough set theory. This extension allows us to use the analog of equivalence queries from exact learning and explore decision trees that are based on various combinations of attributes, hypotheses, and proper hypotheses (analog of proper equivalence queries). The two main goals of this book are (i) to provide tools for the experimental and theoretical study of decision trees with hypotheses and (ii) to compare these decision trees with conventional decision trees that use only queries, each based on a single attribute. Both experimental and theoretical results show that decision trees with hypotheses can have less complexity than conventional decision trees. These results open up some prospects for using decision trees with hypotheses as a means of knowledge representation and algorithms for computing Boolean functions. The obtained theoretical results and tools for studying decision trees with hypotheses are useful for researchers using decision trees and rules in data analysis. This book can also be used as the basis for graduate courses.

Average ratings

N/A

Write a review

Solve jigsaw puzzle

Age

Page Count

148

Publisher

Springer Nature

Published Date

ISBN 10

303108585X

ISBN 13

9783031085857

Extensions of Dynamic Programming for Combinatorial Optimization and Data Mining

By: Hassan AbouEisha,Talha Amin,Igor Chikalov,Shahid Hussain,Mikhail Moshkov

Write a review Read reviews Take a Quiz Solve Book Puzzle

Extensions of Dynamic Programming for Combinatorial Optimization and Data Mining

By: Hassan AbouEisha,Talha Amin,Igor Chikalov,Shahid Hussain,Mikhail Moshkov

Dynamic programming is an efficient technique for solving optimization problems. It is based on breaking the initial problem down into simpler ones and solving these sub-problems, beginning with the simplest ones. A conventional dynamic programming algorithm returns an optimal object from a given set of objects. This book develops extensions of dynamic programming, enabling us to (i) describe the set of objects under consideration; (ii) perform a multi-stage optimization of objects relative to different criteria; (iii) count the number of optimal objects; (iv) find the set of Pareto optimal points for bi-criteria optimization problems; and (v) to study relationships between two criteria. It considers various applications, including optimization of decision trees and decision rule systems as algorithms for problem solving, as ways for knowledge representation, and as classifiers; optimization of element partition trees for rectangular meshes, which are used in finite element methods for solving PDEs; and multi-stage optimization for such classic combinatorial optimization problems as matrix chain multiplication, binary search trees, global sequence alignment, and shortest paths. The results presented are useful for researchers in combinatorial optimization, data mining, knowledge discovery, machine learning, and finite element methods, especially those working in rough set theory, test theory, logical analysis of data, and PDE solvers. This book can be used as the basis for graduate courses.

Average ratings

N/A

Write a review

Solve jigsaw puzzle

Age

Page Count

277

Publisher

Springer

Published Date

ISBN 10

3319918397

ISBN 13

9783319918396

Inhibitory Rules in Data Analysis

A Rough Set Approach

By: Pawel Delimata,Mikhail Ju. Moshkov,Zbigniew Suraj

Write a review Read reviews Take a Quiz Solve Book Puzzle

Inhibitory Rules in Data Analysis

A Rough Set Approach

By: Pawel Delimata,Mikhail Ju. Moshkov,Zbigniew Suraj

This monograph is devoted to theoretical and experimental study of inhibitory decision and association rules. Inhibitory rules contain on the right-hand side a relation of the kind “attribut = value”. The use of inhibitory rules instead of deterministic (standard) ones allows us to describe more completely infor- tion encoded in decision or information systems and to design classi?ers of high quality. The mostimportantfeatureofthis monographis thatit includesanadvanced mathematical analysis of problems on inhibitory rules. We consider algorithms for construction of inhibitory rules, bounds on minimal complexity of inhibitory rules, and algorithms for construction of the set of all minimal inhibitory rules. We also discuss results of experiments with standard and lazy classi?ers based on inhibitory rules. These results show that inhibitory decision and association rules can be used in data mining and knowledge discovery both for knowledge representation and for prediction. Inhibitory rules can be also used under the analysis and design of concurrent systems. The results obtained in the monograph can be useful for researchers in such areas as machine learning, data mining and knowledge discovery, especially for those who are working in rough set theory, test theory, and logical analysis of data (LAD). The monograph can be used under the creation of courses for graduate students and for Ph.D. studies. TheauthorsofthisbookextendanexpressionofgratitudetoProfessorJanusz Kacprzyk, to Dr. Thomas Ditzinger and to the Studies in Computational Int- ligence sta? at Springer for their support in making this book possible.

Average ratings

N/A

Write a review

Solve jigsaw puzzle

Age

Page Count

122

Publisher

Springer Science & Business Media

Published Date

ISBN 10

3540856374

ISBN 13

9783540856375

Partial Covers, Reducts and Decision Rules in Rough Sets

Theory and Applications

By: Mikhail Ju. Moshkov,Marcin Piliszczuk,Beata Zielosko

Write a review Read reviews Take a Quiz Solve Book Puzzle

Partial Covers, Reducts and Decision Rules in Rough Sets

Theory and Applications

By: Mikhail Ju. Moshkov,Marcin Piliszczuk,Beata Zielosko

This book covers the theoretical and experimental study of partial reducts and partial decision rules on the basis of the study of partial covers. It details the results of numerous experiments with randomly generated and real-life decision tables.

Average ratings

N/A

Write a review

Solve jigsaw puzzle

Age

Page Count

158

Publisher

Springer Science & Business Media

Published Date

ISBN 10

3540690271

ISBN 13

9783540690276

Derivative Spectrophotometry and Electron Spin Resonance (ESR) Spectroscopy for Ecological and Biological Questions

By: Vladimir S. Saakov,Valery Z. Drapkin,Alexander I. Krivchenko,Eugene V. Rozengart,Yuri V. Bogachev,Mikhail N. Knyazev

Write a review Read reviews Take a Quiz Solve Book Puzzle

Derivative Spectrophotometry and Electron Spin Resonance (ESR) Spectroscopy for Ecological and Biological Questions

By: Vladimir S. Saakov,Valery Z. Drapkin,Alexander I. Krivchenko,Eugene V. Rozengart,Yuri V. Bogachev,Mikhail N. Knyazev

This book provides a multidisciplinary overview to the application of high order derivative spectrophotometry and Electron Spin Resonance (ESR) spectroscopy in biology and ecology. The characteristics of the principle methods as well as the generation of reliable spectra are discussed in general terms allowing the reader to gain an idea of these methods’ potentials. Furthermore the authors give an extended overview to the spectroscopic and spectro-photometric analysis of specific biological materials. This volume is a well condensed description of an analytical method and a clear review to its application in biology and related fields and an essential tool for researchers who are new in the field of spectroscopic methods and their applications in the life sciences.

Average ratings

N/A

Write a review

Solve jigsaw puzzle

Age

Page Count

373

Publisher

Springer Science & Business Media

Published Date

ISBN 10

3709110068

ISBN 13

9783709110065

Electron Paramagnetic Resonance in Biochemistry and Medicine

By: Rafik Galimzyanovich Sajfutdinov,Lyudmila Ivanovna Larina,Tamara Il'inichna Vakul'skaya,Mikhail Grigor'evich Voronkov

Write a review Read reviews Take a Quiz Solve Book Puzzle

Electron Paramagnetic Resonance in Biochemistry and Medicine

By: Rafik Galimzyanovich Sajfutdinov,Lyudmila Ivanovna Larina,Tamara Il'inichna Vakul'skaya,Mikhail Grigor'evich Voronkov

Electron Paramagnetic Resonance (EPR) spectroscopy - also sometimes termed Electron Spin Resonance spectroscopy - has manifold potential uses in biochemistry and medicine. The paramount importance of EPR spectroscopy applied to biological tissues and fluids is that it identifies the changes in redox processes that contribute to disease. EPR spectroscopy has come a long way from its original use to detect malignant tumors. For example, the development and later refinement of methods of low-temperature registration of biological tissues widened the scope of EPR spectroscopy. Innovations made possible by the introduction of spin labels, probes, and traps made EPR spectroscopy ever more applicable to biochemistry and medicine, to the point where in vivo studies are being carefully considered. This comprehensive book discusses spectra of many tissues and bodily fluids, and the quantitative nature of paramagnetic centers in both normal individuals and patients suffering from a variety of diseases. Special attention is given to the EPR examination of bio-molecules, such as enzymes, polypeptides, vitamins, lipids, hydrocarbons, etc., which play an essential role in human activity. This book will be of great interest to physicians specializing in many different areas. Similarly, biologists, biochemists, biophysicists, and chemists will find this book very useful. It has also been written so that it may be used as a textbook at graduate level.

Average ratings

N/A

Write a review

Solve jigsaw puzzle

Age

Page Count

276

Publisher

Springer Science & Business Media

Published Date

ISBN 10

0306469251

ISBN 13

9780306469251

Geography of Russia and Its Neighbors, Second Edition

By: Mikhail S. Blinnikov

Write a review Read reviews Take a Quiz Solve Book Puzzle

Geography of Russia and Its Neighbors, Second Edition

By: Mikhail S. Blinnikov

Authoritative yet accessible, the definitive undergraduate text on Russian geography and culture has now been thoroughly revised with current data and timely topics, such as the annexation of Crimea and Sevastopol and other background for understanding Russia's 2022 invasion of Ukraine. Thematic chapters provide up-to-date coverage of Russia's physical, political, cultural, and economic geography. Regional chapters focus on the country's major regions and the other 14 former Soviet republics. Written in a lucid, conversational style by a Russian-born international expert, the concise chapters interweave vivid descriptions of urban and rural landscapes, examinations of Soviet and post-Soviet life, deep knowledge of environmental and conservation issues, geopolitical insights, engaging anecdotes, and rigorous empirical data. Over 200 original maps, photographs, and other figures are also available as PowerPoint slides at the companion website, many in color. New to This Edition *Separate chapter on Ukraine and Crimea, covering events through 2019. *Timely topics--the political crisis in Ukraine and annexation of Crimea and Sevastopol; the return of Putin as president; climate change and environmental degradation; economic slowdown; political shifts in the republics; the role of Russian-backed forces in Syria, Libya, and Central African Republic; changes in Russia–United States relations; and more. *Thoroughly updated population, economic, and political data. *80 new or updated figures, tables, and maps. Pedagogical Features *End-of-chapter review questions, suggested assignments, and in-class exercises. *Within-chapter vignettes about Russian places, culture, and history. *End-of-chapter internet resources and suggestions for further reading. *Companion website with all figures and maps from the book, many in full color.

Average ratings

N/A

Write a review

Solve jigsaw puzzle

Age

Page Count

538

Publisher

Guilford Publications

Published Date

ISBN 10

1462544592

ISBN 13

9781462544592

Comparative Analysis of Deterministic and Nondeterministic Decision Trees

By: Mikhail Moshkov

Write a review Read reviews Take a Quiz Solve Book Puzzle

Comparative Analysis of Deterministic and Nondeterministic Decision Trees

By: Mikhail Moshkov

This book compares four parameters of problems in arbitrary information systems: complexity of problem representation and complexity of deterministic, nondeterministic, and strongly nondeterministic decision trees for problem solving. Deterministic decision trees are widely used as classifiers, as a means of knowledge representation, and as algorithms. Nondeterministic (strongly nondeterministic) decision trees can be interpreted as systems of true decision rules that cover all objects (objects from one decision class). This book develops tools for the study of decision trees, including bounds on complexity and algorithms for construction of decision trees for decision tables with many-valued decisions. It considers two approaches to the investigation of decision trees for problems in information systems: local, when decision trees can use only attributes from the problem representation; and global, when decision trees can use arbitrary attributes from the information system. For both approaches, it describes all possible types of relationships among the four parameters considered and discusses the algorithmic problems related to decision tree optimization. The results presented are useful for researchers who apply decision trees and rules to algorithm design and to data analysis, especially those working in rough set theory, test theory and logical analysis of data. This book can also be used as the basis for graduate courses.

Average ratings

N/A

Write a review

Solve jigsaw puzzle

Age

Page Count

297

Publisher

Springer Nature

Published Date

ISBN 10

303041728X

ISBN 13

9783030417284

Combinatorial Machine Learning

A Rough Set Approach

By: Mikhail Moshkov,Beata Zielosko

Write a review Read reviews Take a Quiz Solve Book Puzzle

Combinatorial Machine Learning

A Rough Set Approach

By: Mikhail Moshkov,Beata Zielosko

Average ratings

N/A

Write a review

Solve jigsaw puzzle

Age

Page Count

186

Publisher

Springer

Published Date

ISBN 10

3642209955

ISBN 13

9783642209956

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

By: Fawaz Alsolami,Mohammad Azad,Igor Chikalov,Mikhail Moshkov

Write a review Read reviews Take a Quiz Solve Book Puzzle

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

By: Fawaz Alsolami,Mohammad Azad,Igor Chikalov,Mikhail Moshkov

Average ratings

N/A

Write a review

Solve jigsaw puzzle

Age

Page Count

280

Publisher

Springer

Published Date

ISBN 10

3030128547

ISBN 13

9783030128548

Extensions of Dynamic Programming for Combinatorial Optimization and Data Mining

By: Hassan AbouEisha,Talha Amin,Igor Chikalov,Shahid Hussain,Mikhail Moshkov

Write a review Read reviews Take a Quiz Solve Book Puzzle

Extensions of Dynamic Programming for Combinatorial Optimization and Data Mining

By: Hassan AbouEisha,Talha Amin,Igor Chikalov,Shahid Hussain,Mikhail Moshkov

Average ratings

N/A

Write a review

Solve jigsaw puzzle

Age

Page Count

277

Publisher

Springer

Published Date

ISBN 10

3319918397

ISBN 13

9783319918396

Decision Trees with Hypotheses

By: Mohammad Azad,Igor Chikalov,Shahid Hussain,Mikhail Moshkov,Beata Zielosko

Write a review Read reviews Take a Quiz Solve Book Puzzle

Decision Trees with Hypotheses

By: Mohammad Azad,Igor Chikalov,Shahid Hussain,Mikhail Moshkov,Beata Zielosko

Average ratings

N/A

Write a review

Solve jigsaw puzzle

Age

Page Count

148

Publisher

Springer Nature

Published Date

ISBN 10

303108585X

ISBN 13

9783031085857

Dynamic Programming Multi-Objective Combinatorial Optimization

By: Michal Mankowski,Mikhail Moshkov

Write a review Read reviews Take a Quiz Solve Book Puzzle

Dynamic Programming Multi-Objective Combinatorial Optimization

By: Michal Mankowski,Mikhail Moshkov

Average ratings

N/A

Write a review

Solve jigsaw puzzle

Age

Page Count

213

Publisher

Springer Nature

Published Date

ISBN 10

3030639207

ISBN 13

9783030639204

Comparative Analysis of Deterministic and Nondeterministic Decision Trees

By: Mikhail Moshkov

Write a review Read reviews Take a Quiz Solve Book Puzzle

Comparative Analysis of Deterministic and Nondeterministic Decision Trees

By: Mikhail Moshkov

Average ratings

N/A

Write a review

Solve jigsaw puzzle

Age

Page Count

297

Publisher

Springer Nature

Published Date

ISBN 10

303041728X

ISBN 13

9783030417284

Three Approaches to Data Analysis

Test Theory, Rough Sets and Logical Analysis of Data

By: Igor Chikalov,Vadim Lozin,Irina Lozina,Mikhail Moshkov,Hung Son Nguyen,Andrzej Skowron,Beata Zielosko

Write a review Read reviews Take a Quiz Solve Book Puzzle

Three Approaches to Data Analysis

Test Theory, Rough Sets and Logical Analysis of Data

By: Igor Chikalov,Vadim Lozin,Irina Lozina,Mikhail Moshkov,Hung Son Nguyen,Andrzej Skowron,Beata Zielosko

Average ratings

N/A

Write a review

Solve jigsaw puzzle

Age

Page Count

209

Publisher

Springer Science & Business Media

Published Date

ISBN 10

3642286674

ISBN 13

9783642286674

Decision Trees for Fault Diagnosis in Circuits and Switching Networks

By: Monther Busbait,Mikhail Moshkov,Albina Moshkova,Vladimir Shevtchenko

Write a review Read reviews Take a Quiz Solve Book Puzzle

Decision Trees for Fault Diagnosis in Circuits and Switching Networks

By: Monther Busbait,Mikhail Moshkov,Albina Moshkova,Vladimir Shevtchenko

In this book, we study decision trees for fault diagnosis in circuits and switching networks, which are among the most fundamental models for computing Boolean functions. We consider two main cases: when the scheme (circuit or switching network) has the same mode of operation for both calculation and diagnostics, and when the scheme has two modes of operation—normal for calculation and special for diagnostics. In the former case, we get mostly negative results, including superpolynomial lower bounds on the minimum depth of diagnostic decision trees depending on scheme complexity and the NP-hardness of construction diagnostic decision trees. In the latter case, we describe classes of schemes and types of faults for which decision trees can be effectively used to diagnose schemes, when they are transformed into so-called iteration-free schemes. The tools and results discussed in this book help to understand both the possibilities and challenges of using decision trees to diagnose faults in various schemes. The book is useful to specialists both in the field of theoretical and technical diagnostics.It can also be used for the creation of courses for graduate students.

Average ratings

N/A