Comparative Analysis Deterministic Nondeterministic by Moshkov Mikhail (26 results)
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Published by Springer, 2020
Series: Book 154 of 188 - Intelligent Systems Reference Library
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Series: Book 154 of 188 - Intelligent Systems Reference Library
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Published by Springer, 2021
Series: Book 154 of 188 - Intelligent Systems Reference Library
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Published by Springer, 2020
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Published by Springer, 2020
Series: Book 154 of 188 - Intelligent Systems Reference Library
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Published by Springer, 2020
Series: Book 154 of 188 - Intelligent Systems Reference Library
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Published by Springer, 2021
Series: Book 154 of 188 - Intelligent Systems Reference Library
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Language: English
Published by Springer, 2020
Series: Book 154 of 188 - Intelligent Systems Reference Library
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Language: English
Published by Springer Nature, 2021
Series: Book 154 of 188 - Intelligent Systems Reference Library
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Paperback. Condition: Brand New. 316 pages. 9.25x6.10x0.72 inches. In Stock.
Language: English
Published by Springer Nature, 2020
Series: Book 154 of 188 - Intelligent Systems Reference Library
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Published by Springer International Publishing, 2021
Series: Book 154 of 188 - Intelligent Systems Reference Library
- Softcover
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Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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.
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Language: English
Published by Springer International Publishing, 2020
Series: Book 154 of 188 - Intelligent Systems Reference Library
- Hardcover
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Buch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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 decisi…on 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.
Language: English
Published by Springer, 2021
Series: Book 154 of 188 - Intelligent Systems Reference Library
- Softcover
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Language: English
Published by Springer, 2020
Series: Book 154 of 188 - Intelligent Systems Reference Library
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Language: English
Published by Springer, 2020
Series: Book 154 of 188 - Intelligent Systems Reference Library
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Language: English
Published by Springer, 2021
Series: Book 154 of 188 - Intelligent Systems Reference Library
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Published by Springer International Publishing Mrz 2021, 2021
Series: Book 154 of 188 - Intelligent Systems Reference Library
- Softcover
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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 solvin…g. 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. 316 pp. Englisch.
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Language: English
Published by Springer International Publishing Mrz 2020, 2020
Series: Book 154 of 188 - Intelligent Systems Reference Library
- Hardcover
- Print on Demand
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermanyBuchWeltWeit Ludwig Meier e.K.
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Buch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. Dete…rministic 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. 316 pp. Englisch.
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Language: English
Published by Springer International Publishing, 2021
Series: Book 154 of 188 - Intelligent Systems Reference Library
- Softcover
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Focuses on the comparative analysis of deterministic and nondeterministic decision trees for problems in information systems  Compares the complexity of problem representation and minimum complexities of determini…stic, nondeterministi.
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Language: English
Published by Springer International Publishing, 2020
Series: Book 154 of 188 - Intelligent Systems Reference Library
- Hardcover
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Gebunden. Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Focuses on the comparative analysis of deterministic and nondeterministic decision trees for problems in information systems  Compares the complexity of problem representation and minimum complexities of… deterministic, nondeterministi.
Language: English
Published by Springer, 2021
Series: Book 154 of 188 - Intelligent Systems Reference Library
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Language: English
Published by Springer, 2020
Series: Book 154 of 188 - Intelligent Systems Reference Library
- Hardcover
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Published by Springer, 2021
Series: Book 154 of 188 - Intelligent Systems Reference Library
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Language: English
Published by Springer, 2020
Series: Book 154 of 188 - Intelligent Systems Reference Library
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Published by Springer, Springer Mär 2021, 2021
Series: Book 154 of 188 - Intelligent Systems Reference Library
- Softcover
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -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. D…eterministic 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.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 316 pp. Englisch.
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Language: English
Published by Springer, Springer Mär 2020, 2020
Series: Book 154 of 188 - Intelligent Systems Reference Library
- Hardcover
- Print on Demand
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germanybuchversandmimpf2000
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Buch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -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. Determin…istic 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.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 316 pp. Englisch.
